Recreating Prospectr Alternating Decision Tree Classifier

APPENDIX : CLASSIFIER PERFORMANCE DATA

Recreating Prospectr alternating decision tree classifier

Following instructions http://www.genetics.med.ed.ac.uk/prospectr/download.shtml under section “Replicating PROSPECTR”

ADTREE

Using ADTree –B -15 –E -1 === Run information ===

Scheme: weka.classifiers.trees.ADTree -B 15 -E -1 Relation: training Instances: 2160 Attributes: 65 gene_region stain chips iep family_size exons sigpep transmembrane gene_length cdna_length residue_length gc len_3utr len_5utr a r n d c q e g h i l k m f p s t w y v mouse_identity_x_coverage rat_identity_x_coverage chicken_identity_x_coverage fugu_identity_x_coverage fly_identity_x_coverage worm_identity_x_coverage drerio_identity_x_coverage dog_identity_x_coverage bee_identity_x_coverage drerio_identity dog_identity bee_identity frog_identity mouse_identity rat_identity chicken_identity fugu_identity fly_identity worm_identity mosquito_identity tetraodon_identity mouse_dnds mouse_dn mouse_ds rat_dnds paralog_identity_x_coverage paralog_identity mouse_upstreams rat_upstreams chicken_upstreams phenotype Test mode: user supplied test set: 2160 instances

=== Classifier model (full training set) ===

Alternating decision tree:

Time taken to build model: 4.67 seconds

=== Evaluation on test set ======Summary ===

Correctly Classified Instances 1528 70.7407 % Incorrectly Classified Instances 632 29.2593 % Kappa statistic 0.4148 Mean absolute error 0.4161 Root mean squared error 0.4407 Relative absolute error 83.2226 % Root relative squared error 88.1404 % Total Number of Instances 2160

=== Detailed Accuracy By Class ===

TP Rate FP Rate Precision Recall F-Measure Class 0.731 0.317 0.698 0.731 0.714 disease 0.683 0.269 0.718 0.683 0.7 normal

=== Confusion Matrix ===

a b <-- classified as 790 290 | a = disease 342 738 | b = normal

HGMD

=== Evaluation on test set ======Summary ===

Correctly Classified Instances 915 64.1655 % Incorrectly Classified Instances 511 35.8345 % Kappa statistic 0.2833 Mean absolute error 0.4395 Root mean squared error 0.4634 Relative absolute error 87.9095 % Root relative squared error 92.6743 % Total Number of Instances 1426

=== Detailed Accuracy By Class ===

TP Rate FP Rate Precision Recall F-Measure Class 0.663 0.38 0.636 0.663 0.649 disease 0.62 0.337 0.648 0.62 0.634 normal

=== Confusion Matrix ===

a b <-- classified as 473 240 | a = disease 271 442 | b = normal

POCUS

== Evaluation on test set ======Summary ===

Correctly Classified Instances 70 70 % Incorrectly Classified Instances 30 30 % Kappa statistic 0.4 Mean absolute error 0.4099 Root mean squared error 0.4338 Relative absolute error 81.9798 % Root relative squared error 86.7533 % Total Number of Instances 100

=== Detailed Accuracy By Class ===

TP Rate FP Rate Precision Recall F-Measure Class 0.72 0.32 0.692 0.72 0.706 disease 0.68 0.28 0.708 0.68 0.694 normal === Confusion Matrix ===

a b <-- classified as 36 14 | a = disease 16 34 | b = normal

SELF_REDUCED

=== Run information ===

Scheme: weka.classifiers.trees.ADTree -B 15 -E -1 Relation: training-weka.filters.unsupervised.attribute.Remove-R1-5,15-47,50-52,54-60,62-64 Instances: 2160 Attributes: 14 exons sigpep transmembrane gene_length cdna_length residue_length gc len_3utr len_5utr mouse_identity rat_identity worm_identity paralog_identity phenotype Test mode: user supplied test set: 2160 instances

=== Classifier model (full training set) ===

Alternating decision tree:

Time taken to build model: 0.74 seconds

=== Evaluation on test set ======Summary ===

Correctly Classified Instances 1460 67.5926 % Incorrectly Classified Instances 700 32.4074 % Kappa statistic 0.3519 Mean absolute error 0.4244 Root mean squared error 0.4485 Relative absolute error 84.8737 % Root relative squared error 89.7059 % Total Number of Instances 2160

=== Detailed Accuracy By Class ===

TP Rate FP Rate Precision Recall F-Measure Class 0.743 0.391 0.655 0.743 0.696 disease 0.609 0.257 0.703 0.609 0.653 normal

=== Confusion Matrix ===

a b <-- classified as 802 278 | a = disease 422 658 | b = normal

HGMD_REDUCED === Evaluation on test set ======Summary ===

Correctly Classified Instances 896 62.8331 % Incorrectly Classified Instances 530 37.1669 % Kappa statistic 0.2567 Mean absolute error 0.4415 Root mean squared error 0.4652 Relative absolute error 88.2981 % Root relative squared error 93.0462 % Total Number of Instances 1426

=== Detailed Accuracy By Class ===

TP Rate FP Rate Precision Recall F-Measure Class 0.69 0.433 0.614 0.69 0.65 disease 0.567 0.31 0.646 0.567 0.604 normal

=== Confusion Matrix ===

a b <-- classified as 492 221 | a = disease 309 404 | b = normal

POCUS_REDUCED === Evaluation on test set ======Summary ===

Correctly Classified Instances 72 72 % Incorrectly Classified Instances 28 28 % Kappa statistic 0.44 Mean absolute error 0.4145 Root mean squared error 0.441 Relative absolute error 82.8984 % Root relative squared error 88.1979 % Total Number of Instances 100

=== Detailed Accuracy By Class ===

TP Rate FP Rate Precision Recall F-Measure Class 0.74 0.3 0.712 0.74 0.725 disease 0.7 0.26 0.729 0.7 0.714 normal

=== Confusion Matrix ===

a b <-- classified as 37 13 | a = disease 15 35 | b = normal J48

SELF === Run information ===

Scheme: weka.classifiers.trees.J48 -C 0.25 -M 5 Relation: training Instances: 2160 Attributes: 65 gene_region stain chips iep family_size exons sigpep transmembrane gene_length cdna_length residue_length gc len_3utr len_5utr a r n d c q e g h i l k m f p s t w y v mouse_identity_x_coverage rat_identity_x_coverage chicken_identity_x_coverage fugu_identity_x_coverage fly_identity_x_coverage worm_identity_x_coverage drerio_identity_x_coverage dog_identity_x_coverage bee_identity_x_coverage drerio_identity dog_identity bee_identity frog_identity mouse_identity rat_identity chicken_identity fugu_identity fly_identity worm_identity mosquito_identity tetraodon_identity mouse_dnds mouse_dn mouse_ds rat_dnds paralog_identity_x_coverage paralog_identity mouse_upstreams rat_upstreams chicken_upstreams phenotype Test mode: user supplied test set: 2160 instances

=== Classifier model (full training set) ===

Number of Leaves : 138

Size of the tree : 275

Time taken to build model: 2.61 seconds

=== Evaluation on test set ======Summary ===

Correctly Classified Instances 1917 88.75 % Incorrectly Classified Instances 243 11.25 % Kappa statistic 0.775 Mean absolute error 0.1626 Root mean squared error 0.2833 Relative absolute error 32.5172 % Root relative squared error 56.6663 % Total Number of Instances 2160

=== Detailed Accuracy By Class ===

TP Rate FP Rate Precision Recall F-Measure Class 0.924 0.149 0.861 0.924 0.891 disease 0.851 0.076 0.918 0.851 0.883 normal

=== Confusion Matrix ===

a b <-- classified as 998 82 | a = disease 161 919 | b = normal

HGMD === Evaluation on test set ======Summary ===

Correctly Classified Instances 902 63.2539 % Incorrectly Classified Instances 524 36.7461 % Kappa statistic 0.2651 Mean absolute error 0.3716 Root mean squared error 0.5312 Relative absolute error 74.323 % Root relative squared error 106.2381 % Total Number of Instances 1426

=== Detailed Accuracy By Class ===

TP Rate FP Rate Precision Recall F-Measure Class 0.641 0.376 0.63 0.641 0.636 disease 0.624 0.359 0.635 0.624 0.629 normal

=== Confusion Matrix ===

a b <-- classified as 457 256 | a = disease 268 445 | b = normal POCUS === Evaluation on test set ======Summary ===

Correctly Classified Instances 65 65 % Incorrectly Classified Instances 35 35 % Kappa statistic 0.3 Mean absolute error 0.3681 Root mean squared error 0.5333 Relative absolute error 73.6147 % Root relative squared error 106.6551 % Total Number of Instances 100

=== Detailed Accuracy By Class ===

TP Rate FP Rate Precision Recall F-Measure Class 0.68 0.38 0.642 0.68 0.66 disease 0.62 0.32 0.66 0.62 0.639 normal

=== Confusion Matrix ===

a b <-- classified as 34 16 | a = disease 19 31 | b = normal

SELF_REDUCED === Run information ===

Scheme: weka.classifiers.trees.J48 -C 0.25 -M 5 Relation: training-weka.filters.unsupervised.attribute.Remove-R1-5,15-47,50-52,54-60,62-64 Instances: 2160 Attributes: 14 exons sigpep transmembrane gene_length cdna_length residue_length gc len_3utr len_5utr mouse_identity rat_identity worm_identity paralog_identity phenotype Test mode: user supplied test set: 2160 instances

=== Classifier model (full training set) ===

Number of Leaves : 48

Size of the tree : 95

Time taken to build model: 0.28 seconds

=== Evaluation on test set ======Summary ===

Correctly Classified Instances 1591 73.6574 % Incorrectly Classified Instances 569 26.3426 % Kappa statistic 0.4731 Mean absolute error 0.3368 Root mean squared error 0.4104 Relative absolute error 67.3569 % Root relative squared error 82.0712 % Total Number of Instances 2160

=== Detailed Accuracy By Class ===

TP Rate FP Rate Precision Recall F-Measure Class 0.84 0.367 0.696 0.84 0.761 disease 0.633 0.16 0.798 0.633 0.706 normal

=== Confusion Matrix ===

a b <-- classified as 907 173 | a = disease 396 684 | b = normal

HGMD_REDUCED === Evaluation on test set ======Summary ===

Correctly Classified Instances 856 60.0281 % Incorrectly Classified Instances 570 39.9719 % Kappa statistic 0.2006 Mean absolute error 0.414 Root mean squared error 0.4904 Relative absolute error 82.7972 % Root relative squared error 98.0798 % Total Number of Instances 1426

=== Detailed Accuracy By Class ===

TP Rate FP Rate Precision Recall F-Measure Class 0.679 0.478 0.587 0.679 0.629 disease 0.522 0.321 0.619 0.522 0.566 normal

=== Confusion Matrix ===

a b <-- classified as 484 229 | a = disease 341 372 | b = normal POCUS_REDUCED === Evaluation on test set ======Summary ===

Correctly Classified Instances 71 71 % Incorrectly Classified Instances 29 29 % Kappa statistic 0.42 Mean absolute error 0.3789 Root mean squared error 0.4509 Relative absolute error 75.7779 % Root relative squared error 90.1713 % Total Number of Instances 100

=== Detailed Accuracy By Class ===

TP Rate FP Rate Precision Recall F-Measure Class 0.8 0.38 0.678 0.8 0.734 disease 0.62 0.2 0.756 0.62 0.681 normal

=== Confusion Matrix ===

a b <-- classified as 40 10 | a = disease 19 31 | b = normal mouse_dn Logistic mouse_ds rat_dnds paralog_identity_x_coverage paralog_identity Self mouse_upstreams rat_upstreams === Run information === chicken_upstreams phenotype Scheme: weka.classifiers.functions.Logistic -R 1.0E-8 -M -1 Test mode: user supplied test set: 2160 instances Relation: training Instances: 2160 === Classifier model (full training set) === Attributes: 65 gene_region Logistic Regression with ridge parameter of 1.0E-8 stain Coefficients... chips Variable Coeff. iep 1 -0.0014 family_size 2 -0.0115 exons 3 -1.8095 sigpep 4 -0.0027 transmembrane 5 0.0213 gene_length 6 1.0978 cdna_length 7 -0.2428 residue_length 8 0 gc 9 -0.0049 len_3utr 10 0.0146 len_5utr 11 0.0054 a 12 0.0047 r 13 0.0052 n 14 -0.1132 d 15 -0.2335 c 16 -0.0667 q 17 -0.1212 e 18 -0.1446 g 19 -0.1305 h 20 -0.1389 i 21 -0.0842 l 22 -0.1717 k 23 -0.1323 m 24 -0.1365 f 25 -0.1493 p 26 -0.1139 s 27 -0.1287 t 28 -0.1474 w 29 -0.1684 y 30 -0.143 v 31 -0.0961 mouse_identity_x_coverage 32 -0.1236 rat_identity_x_coverage 33 -0.1663 chicken_identity_x_coverage 34 0.0145 fugu_identity_x_coverage 35 0.0094 fly_identity_x_coverage 36 -0.0185 worm_identity_x_coverage 37 0.0051 drerio_identity_x_coverage 38 -0.0215 dog_identity_x_coverage 39 0.0309 bee_identity_x_coverage 40 0.0052 drerio_identity 41 -0.0063 dog_identity 42 0.0029 bee_identity 43 -0.0025 frog_identity 44 0.0126 mouse_identity 45 -0.0048 rat_identity 46 0.0069 chicken_identity 47 -0.0077 fugu_identity 48 -0.0002 fly_identity 49 0.017 worm_identity 50 0 mosquito_identity 51 0.0075 tetraodon_identity 52 -0.0188 mouse_dnds 53 0.0077 54 0.0015 39 1.0314 55 0.3639 40 1.0053 56 2.7838 41 0.9937 57 0.6007 42 1.0029 58 0.3708 43 0.9975 59 0.0001 44 1.0126 60 -0.0001 45 0.9952 61 0 46 1.0069 Intercept 19.4004 47 0.9923 48 0.9998 Odds Ratios... 49 1.0172 Variable O.R. 50 1 1 0.9986 51 1.0075 2 0.9886 52 0.9814 3 0.1637 53 1.0078 4 0.9973 54 1.0015 5 1.0215 55 1.4389 6 2.9977 56 16.1803 7 0.7844 57 1.8233 8 1 58 1.4489 9 0.9951 59 1.0001 10 1.0147 60 0.9999 11 1.0054 61 1 12 1.0048 13 1.0052 14 0.893 Time taken to build model: 1.63 seconds 15 0.7918 16 0.9354 === Evaluation on test set === 17 0.8859 === Summary === 18 0.8654 19 0.8777 Correctly Classified Instances 1512 70 % 20 0.8703 Incorrectly Classified Instances 648 30 % 21 0.9193 Kappa statistic 0.4 22 0.8423 Mean absolute error 0.3757 23 0.8761 Root mean squared error 0.4338 24 0.8724 Relative absolute error 75.1415 % 25 0.8613 Root relative squared error 86.7601 % 26 0.8923 Total Number of Instances 2160 27 0.8792 28 0.8629 === Detailed Accuracy By Class === 29 0.845 30 0.8668 TP Rate FP Rate Precision Recall F-Measure Class 31 0.9084 0.736 0.336 0.687 0.736 0.71 disease 32 0.8837 0.664 0.264 0.716 0.664 0.689 normal 33 0.8468 34 1.0146 === Confusion Matrix === 35 1.0094 36 0.9816 a b <-- classified as 37 1.0051 795 285 | a = disease 38 0.9788 363 717 | b = normal

HGMD_TEST

=== Evaluation on test set ======Summary ===

Correctly Classified Instances 914 64.0954 % Incorrectly Classified Instances 512 35.9046 % Kappa statistic 0.2819 Mean absolute error 0.4125 Root mean squared error 0.4685 Relative absolute error 82.503 % Root relative squared error 93.6964 % Total Number of Instances 1426

=== Detailed Accuracy By Class === TP Rate FP Rate Precision Recall F-Measure Class 0.669 0.387 0.633 0.669 0.651 disease 0.613 0.331 0.649 0.613 0.631 normal

=== Confusion Matrix ===

a b <-- classified as 477 236 | a = disease 276 437 | b = normal

POCUS === Evaluation on test set ======Summary ===

Correctly Classified Instances 69 69 % Incorrectly Classified Instances 31 31 % Kappa statistic 0.38 Mean absolute error 0.3679 Root mean squared error 0.4269 Relative absolute error 73.5737 % Root relative squared error 85.3806 % Total Number of Instances 100

=== Detailed Accuracy By Class ===

TP Rate FP Rate Precision Recall F-Measure Class 0.72 0.34 0.679 0.72 0.699 disease 0.66 0.28 0.702 0.66 0.68 normal

=== Confusion Matrix ===

a b <-- classified as 36 14 | a = disease 17 33 | b = normal

SELF_REDUCED === Run information === 2 1.2965 3 -0.1223 Scheme: weka.classifiers.functions.Logistic -R 1.0E-8 -M -1 4 0 Relation: training-weka.filters.unsupervised.attribute.Remove- 5 0.0082 R1-5,15-47,50-52,54-60,62-64 6 -0.0244 Instances: 2160 7 0.0077 Attributes: 14 8 -0.0082 exons 9 -0.0079 sigpep 10 0.0136 transmembrane 11 0.0092 gene_length 12 0.0069 cdna_length Intercept -2.8036 residue_length gc Odds Ratios... len_3utr Variable O.R. len_5utr 1 1.0288 mouse_identity 2 3.6566 rat_identity 3 0.8849 worm_identity 4 1 paralog_identity 5 1.0082 phenotype 6 0.9759 Test mode: user supplied test set: 2160 instances 7 1.0078 8 0.9919 === Classifier model (full training set) === 9 0.9921 10 1.0137 Logistic Regression with ridge parameter of 1.0E-8 11 1.0092 Coefficients... 12 1.0069 Variable Coeff. 1 0.0284 Time taken to build model: 0.44 seconds === Detailed Accuracy By Class ======Evaluation on test set ======Summary === TP Rate FP Rate Precision Recall F-Measure Class 0.691 0.389 0.64 0.691 0.664 disease Correctly Classified Instances 1406 65.0926 % 0.611 0.309 0.664 0.611 0.636 normal Incorrectly Classified Instances 754 34.9074 % Kappa statistic 0.3019 === Confusion Matrix === Mean absolute error 0.4125 Root mean squared error 0.4549 a b <-- classified as Relative absolute error 82.4911 % 746 334 | a = disease Root relative squared error 90.9701 % 420 660 | b = normal Total Number of Instances 2160

HGMD_REDUCED === Evaluation on test set ======Summary ===

Correctly Classified Instances 884 61.9916 % Incorrectly Classified Instances 542 38.0084 % Kappa statistic 0.2398 Mean absolute error 0.4321 Root mean squared error 0.4721 Relative absolute error 86.4113 % Root relative squared error 94.4237 % Total Number of Instances 1426

=== Detailed Accuracy By Class ===

TP Rate FP Rate Precision Recall F-Measure Class 0.634 0.394 0.617 0.634 0.625 disease 0.606 0.366 0.623 0.606 0.615 normal

=== Confusion Matrix ===

a b <-- classified as 452 261 | a = disease 281 432 | b = normal

POCUS_REDUCED === Evaluation on test set ======Summary ===

Correctly Classified Instances 65 65 % Incorrectly Classified Instances 35 35 % Kappa statistic 0.3 Mean absolute error 0.4138 Root mean squared error 0.4534 Relative absolute error 82.7688 % Root relative squared error 90.6841 % Total Number of Instances 100

=== Detailed Accuracy By Class === TP Rate FP Rate Precision Recall F-Measure Class 0.74 0.44 0.627 0.74 0.679 disease 0.56 0.26 0.683 0.56 0.615 normal

=== Confusion Matrix === a b <-- classified as 37 13 | a = disease 22 28 | b = normal SMO SMO -C 1.0 -E 1.0 -G 0.01 -A 250007 -L 0.0010 -P 1.0E-12 -N 0 -V -1 -W 1

SELF === Run information === mouse_dnds mouse_dn Scheme: weka.classifiers.functions.SMO -C 1.0 -E 1.0 -G 0.01 mouse_ds -A 250007 -L 0.0010 -P 1.0E-12 -N 0 -V -1 -W 1 rat_dnds Relation: training paralog_identity_x_coverage Instances: 2160 paralog_identity Attributes: 65 mouse_upstreams gene_region rat_upstreams stain chicken_upstreams chips phenotype iep Test mode: user supplied test set: 2160 instances family_size exons === Classifier model (full training set) === sigpep transmembrane SMO gene_length cdna_length Classifier for classes: disease, normal residue_length gc BinarySMO len_3utr len_5utr Machine linear: showing attribute weights, not support vectors. a r 0.4297 * (normalized) gene_region n + 0.8224 * (normalized) chips d + 2.4756 * (normalized) iep c + 0.6277 * (normalized) family_size q + -1.4416 * (normalized) exons e + -0.8978 * (normalized) sigpep g + 0.2201 * (normalized) transmembrane h + -0.8294 * (normalized) gene_length i + -0.3847 * (normalized) cdna_length l + -0.4514 * (normalized) residue_length k + -0.588 * (normalized) gc m + 1.0552 * (normalized) len_3utr f + -0.7991 * (normalized) len_5utr p + -0.7217 * (normalized) a s + 2.6448 * (normalized) r t + -0.8713 * (normalized) n w + -0.2684 * (normalized) d y + 0.0093 * (normalized) c v + -0.3171 * (normalized) q mouse_identity_x_coverage + -0.3083 * (normalized) e rat_identity_x_coverage + -1.8044 * (normalized) g chicken_identity_x_coverage + 0.3953 * (normalized) h fugu_identity_x_coverage + -0.6702 * (normalized) i fly_identity_x_coverage + -0.3671 * (normalized) l worm_identity_x_coverage + 0.1901 * (normalized) k drerio_identity_x_coverage + -0.423 * (normalized) m dog_identity_x_coverage + 0.0627 * (normalized) f bee_identity_x_coverage + 0.3155 * (normalized) p drerio_identity + 0.1543 * (normalized) s dog_identity + -0.1996 * (normalized) t bee_identity + -0.4942 * (normalized) w frog_identity + 0.0414 * (normalized) y mouse_identity + -0.3158 * (normalized) v rat_identity + -1.5004 * (normalized) mouse_identity_x_coverage chicken_identity + -0.7441 * (normalized) rat_identity_x_coverage fugu_identity + 1.4074 * (normalized) chicken_identity_x_coverage fly_identity + -0.683 * (normalized) fugu_identity_x_coverage worm_identity + 1.0504 * (normalized) fly_identity_x_coverage mosquito_identity + -1.4547 * (normalized) worm_identity_x_coverage tetraodon_identity + -0.4016 * (normalized) drerio_identity_x_coverage + 0.3734 * (normalized) dog_identity_x_coverage + 0.0785 * (normalized) bee_identity_x_coverage Time taken to build model: 4.83 seconds + 0.1333 * (normalized) drerio_identity + -0.68 * (normalized) dog_identity === Evaluation on test set === + 0.1914 * (normalized) bee_identity === Summary === + -0.7651 * (normalized) frog_identity + 1.1931 * (normalized) mouse_identity Correctly Classified Instances 1534 71.0185 % + 0.0313 * (normalized) rat_identity Incorrectly Classified Instances 626 28.9815 % + -1.2135 * (normalized) chicken_identity Kappa statistic 0.4204 + -0.1479 * (normalized) fugu_identity Mean absolute error 0.2898 + -0.0615 * (normalized) fly_identity Root mean squared error 0.5383 + 0.6449 * (normalized) worm_identity Relative absolute error 57.963 % + -0.6326 * (normalized) mosquito_identity Root relative squared error 107.6689 % + -0.0567 * (normalized) tetraodon_identity Total Number of Instances 2160 + -0.6087 * (normalized) mouse_dnds + -1.0755 * (normalized) mouse_dn === Detailed Accuracy By Class === + -0.622 * (normalized) mouse_ds + -0.6734 * (normalized) rat_dnds TP Rate FP Rate Precision Recall F-Measure Class + -0.7953 * (normalized) mouse_upstreams 0.79 0.369 0.681 0.79 0.732 disease + 0.4563 * (normalized) rat_upstreams 0.631 0.21 0.75 0.631 0.685 normal + 0.5878 * (normalized) chicken_upstreams + 1.7676 === Confusion Matrix ===

Number of kernel evaluations: 1393616 (76.963% cached) a b <-- classified as 853 227 | a = disease 399 681 | b = normal

HGMD === Evaluation on test set ======Summary ===

Correctly Classified Instances 926 64.9369 % Incorrectly Classified Instances 500 35.0631 % Kappa statistic 0.2987 Mean absolute error 0.3506 Root mean squared error 0.5921 Relative absolute error 70.1262 % Root relative squared error 118.4282 % Total Number of Instances 1426

=== Detailed Accuracy By Class ===

TP Rate FP Rate Precision Recall F-Measure Class 0.719 0.421 0.631 0.719 0.672 disease 0.579 0.281 0.674 0.579 0.623 normal

=== Confusion Matrix ===

a b <-- classified as 513 200 | a = disease 300 413 | b = normal

POCUS === Evaluation on test set ======Summary ===

Correctly Classified Instances 72 72 % Incorrectly Classified Instances 28 28 % Kappa statistic 0.44 Mean absolute error 0.28 Root mean squared error 0.5292 Relative absolute error 56 % Root relative squared error 105.8301 % Total Number of Instances 100 === Detailed Accuracy By Class ===

TP Rate FP Rate Precision Recall F-Measure Class 0.82 0.38 0.683 0.82 0.745 disease 0.62 0.18 0.775 0.62 0.689 normal

=== Confusion Matrix ===

a b <-- classified as 41 9 | a = disease 19 31 | b = normal

SELF_REDUCED === Run information === + -1.3272 * (normalized) residue_length + -0.4142 * (normalized) gc Scheme: weka.classifiers.functions.SMO -C 1.0 -E 1.0 -G 0.01 + 0.2138 * (normalized) len_3utr -A 250007 -L 0.0010 -P 1.0E-12 -N 0 -V -1 -W 1 + -0.6791 * (normalized) len_5utr Relation: training-weka.filters.unsupervised.attribute.Remove- + -0.7207 * (normalized) mouse_identity R1-5,15-47,50-52,54-60,62-64 + -0.8092 * (normalized) rat_identity Instances: 2160 + -1.687 * (normalized) worm_identity Attributes: 14 + 1.9688 exons sigpep Number of kernel evaluations: 439479 (69.864% cached) transmembrane gene_length cdna_length residue_length Time taken to build model: 0.86 seconds gc len_3utr === Evaluation on test set === len_5utr === Summary === mouse_identity rat_identity Correctly Classified Instances 1408 65.1852 % worm_identity Incorrectly Classified Instances 752 34.8148 % paralog_identity Kappa statistic 0.3037 phenotype Mean absolute error 0.3481 Test mode: user supplied test set: 2160 instances Root mean squared error 0.59 Relative absolute error 69.6296 % === Classifier model (full training set) === Root relative squared error 118.0082 % Total Number of Instances 2160 SMO === Detailed Accuracy By Class === Classifier for classes: disease, normal TP Rate FP Rate Precision Recall F-Measure Class BinarySMO 0.647 0.344 0.653 0.647 0.65 disease 0.656 0.353 0.65 0.656 0.653 normal Machine linear: showing attribute weights, not support vectors. === Confusion Matrix === -3.3591 * (normalized) exons + -1.4006 * (normalized) sigpep a b <-- classified as + 0.1842 * (normalized) transmembrane 699 381 | a = disease + -1.0541 * (normalized) gene_length 371 709 | b = normal + -1.3226 * (normalized) cdna_length

HGMD_REDUCED === Evaluation on test set ======Summary ===

Correctly Classified Instances 909 63.7447 % Incorrectly Classified Instances 517 36.2553 % Kappa statistic 0.2749 Mean absolute error 0.3626 Root mean squared error 0.6021 Relative absolute error 72.5105 % Root relative squared error 120.4247 % Total Number of Instances 1426

=== Detailed Accuracy By Class ===

TP Rate FP Rate Precision Recall F-Measure Class 0.613 0.338 0.645 0.613 0.628 disease 0.662 0.387 0.631 0.662 0.646 normal

=== Confusion Matrix ===

a b <-- classified as 437 276 | a = disease 241 472 | b = normal

POCUS_REDUCED === Evaluation on test set ======Summary ===

Correctly Classified Instances 66 66 % Incorrectly Classified Instances 34 34 % Kappa statistic 0.32 Mean absolute error 0.34 Root mean squared error 0.5831 Relative absolute error 68 % Root relative squared error 116.619 % Total Number of Instances 100

=== Detailed Accuracy By Class ===

TP Rate FP Rate Precision Recall F-Measure Class 0.7 0.38 0.648 0.7 0.673 disease 0.62 0.3 0.674 0.62 0.646 normal

=== Confusion Matrix ===

a b <-- classified as 35 15 | a = disease 19 31 | b = normal Naïve Bayes

SELF === Run information === mouse_dn mouse_ds Scheme: weka.classifiers.bayes.NaiveBayes rat_dnds Relation: training paralog_identity_x_coverage Instances: 2160 paralog_identity Attributes: 65 mouse_upstreams gene_region rat_upstreams stain chicken_upstreams chips phenotype iep Test mode: user supplied test set: 2160 instances family_size exons === Classifier model (full training set) === sigpep transmembrane Naive Bayes Classifier gene_length cdna_length Class disease: Prior probability = 0.5 residue_length gc gene_region: Normal Distribution. Mean = 17.1507 StandardDev len_3utr = 13.011 WeightSum = 1080 Precision = 1.1833333333333333 len_5utr stain: Discrete Estimator. Counts = 1081 1 1 1 1 1 (Total = 1086) a chips: Normal Distribution. Mean = 51.6777 StandardDev = r 4.6665 WeightSum = 1080 Precision = 0.022233706720977596 n iep: Normal Distribution. Mean = 4.6319 StandardDev = 0.1518 d WeightSum = 1080 Precision = 0.0015156637168141592 c family_size: Normal Distribution. Mean = 5.6734 StandardDev = q 22.5043 WeightSum = 1080 Precision = 11.738095238095237 e exons: Normal Distribution. Mean = 14.3018 StandardDev = g 15.778 WeightSum = 1080 Precision = 4.597014925373134 h sigpep: Discrete Estimator. Counts = 695 387 (Total = 1082) i transmembrane: Discrete Estimator. Counts = 770 312 (Total = l 1082) k gene_length: Normal Distribution. Mean = 68736.0066 m StandardDev = 138185.4067 WeightSum = 1080 Precision = f 1000.0119502868068 p cdna_length: Normal Distribution. Mean = 3151.1808 s StandardDev = 3740.5714 WeightSum = 1080 Precision = t 57.99126383226558 w residue_length: Normal Distribution. Mean = 713.4124 y StandardDev = 1173.8511 WeightSum = 1080 Precision = v 32.10088148873653 mouse_identity_x_coverage gc: Normal Distribution. Mean = 46.6465 StandardDev = 8.3407 rat_identity_x_coverage WeightSum = 1080 Precision = 1.5555555555555556 chicken_identity_x_coverage len_3utr: Normal Distribution. Mean = 830.5971 StandardDev = fugu_identity_x_coverage 1042.2274 WeightSum = 1080 Precision = 7.88860544217687 fly_identity_x_coverage len_5utr: Normal Distribution. Mean = 178.3895 StandardDev = worm_identity_x_coverage 272.2791 WeightSum = 1080 Precision = 8.4348623853211 drerio_identity_x_coverage a: Normal Distribution. Mean = 7.2881 StandardDev = 2.56 dog_identity_x_coverage WeightSum = 1080 Precision = 0.013338397328881469 bee_identity_x_coverage r: Normal Distribution. Mean = 5.3506 StandardDev = 1.8648 drerio_identity WeightSum = 1080 Precision = 0.023054755043227664 dog_identity n: Normal Distribution. Mean = 3.6973 StandardDev = 1.4776 bee_identity WeightSum = 1080 Precision = 0.006994470868014268 frog_identity d: Normal Distribution. Mean = 4.7253 StandardDev = 1.6131 mouse_identity WeightSum = 1080 Precision = 0.011417650496785505 rat_identity c: Normal Distribution. Mean = 2.3947 StandardDev = 1.9859 chicken_identity WeightSum = 1080 Precision = 0.020201417128773876 fugu_identity q: Normal Distribution. Mean = 4.3851 StandardDev = 1.7085 fly_identity WeightSum = 1080 Precision = 0.011222980997624704 worm_identity e: Normal Distribution. Mean = 6.4778 StandardDev = 2.4427 mosquito_identity WeightSum = 1080 Precision = 0.020908027133973998 tetraodon_identity g: Normal Distribution. Mean = 7.3957 StandardDev = 3.4498 mouse_dnds WeightSum = 1080 Precision = 0.017684966216216215 h: Normal Distribution. Mean = 2.4531 StandardDev = 1.1396 fly_identity: Normal Distribution. Mean = 16.5306 StandardDev = WeightSum = 1080 Precision = 0.01905213622291022 24.8585 WeightSum = 1080 Precision = 1.434782608695652 i: Normal Distribution. Mean = 4.5457 StandardDev = 1.9027 worm_identity: Normal Distribution. Mean = 13.7456 WeightSum = 1080 Precision = 0.010016030092592594 StandardDev = 22.4936 WeightSum = 1080 Precision = l: Normal Distribution. Mean = 9.9015 StandardDev = 2.6816 1.5714285714285714 WeightSum = 1080 Precision = 0.01193805260212647 mosquito_identity: Normal Distribution. Mean = 17.5149 k: Normal Distribution. Mean = 5.5458 StandardDev = 2.3546 StandardDev = 26.1788 WeightSum = 1080 Precision = WeightSum = 1080 Precision = 0.015546918378678512 1.4142857142857144 m: Normal Distribution. Mean = 2.2942 StandardDev = 0.9328 tetraodon_identity: Normal Distribution. Mean = 49.5655 WeightSum = 1080 Precision = 0.0076045627376425855 StandardDev = 27.9196 WeightSum = 1080 Precision = f: Normal Distribution. Mean = 3.9849 StandardDev = 1.624 1.2820512820512822 WeightSum = 1080 Precision = 0.019527416520210897 mouse_dnds: Normal Distribution. Mean = 0.134 StandardDev = p: Normal Distribution. Mean = 6.1309 StandardDev = 3.1327 0.1219 WeightSum = 1000 Precision = 9.242306544202066E-4 WeightSum = 1080 Precision = 0.023772330911123532 mouse_dn: Normal Distribution. Mean = 0.0858 StandardDev = s: Normal Distribution. Mean = 7.5964 StandardDev = 2.5847 0.081 WeightSum = 1000 Precision = 6.754816112084063E-4 WeightSum = 1080 Precision = 0.022804775280898876 mouse_ds: Normal Distribution. Mean = 0.636 StandardDev = t: Normal Distribution. Mean = 5.2385 StandardDev = 1.4792 0.2139 WeightSum = 1000 Precision = 7.490019317450097E-4 WeightSum = 1080 Precision = 0.01249046762589928 rat_dnds: Normal Distribution. Mean = 0.1315 StandardDev = w: Normal Distribution. Mean = 1.3618 StandardDev = 0.8966 0.1137 WeightSum = 945 Precision = 7.33667564259486E-4 WeightSum = 1080 Precision = 0.006006487406398911 paralog_identity_x_coverage: Normal Distribution. Mean = 0 y: Normal Distribution. Mean = 2.9664 StandardDev = 1.2475 StandardDev = 0.0017 WeightSum = 1080 Precision = 0.01 WeightSum = 1080 Precision = 0.00726216049382716 paralog_identity: Normal Distribution. Mean = 0 StandardDev = v: Normal Distribution. Mean = 6.2651 StandardDev = 1.8631 0.0017 WeightSum = 1080 Precision = 0.01 WeightSum = 1080 Precision = 0.010865994236311238 mouse_upstreams: Normal Distribution. Mean = 931.4325 mouse_identity_x_coverage: Normal Distribution. Mean = StandardDev = 1199.9255 WeightSum = 906 Precision = 77.9234 StandardDev = 21.2948 WeightSum = 1080 Precision = 10.021350407450525 0.20833333333333334 rat_upstreams: Normal Distribution. Mean = 888.9607 rat_identity_x_coverage: Normal Distribution. Mean = 72.4664 StandardDev = 1133.7195 WeightSum = 875 Precision = StandardDev = 26.0226 WeightSum = 1080 Precision = 10.307165871121716 0.17421602787456447 chicken_upstreams: Normal Distribution. Mean = 340.4675 chicken_identity_x_coverage: Normal Distribution. Mean = StandardDev = 327.3591 WeightSum = 231 Precision = 48.2194 StandardDev = 30.9691 WeightSum = 1080 Precision = 6.690600000000001 0.13297872340425532 fugu_identity_x_coverage: Normal Distribution. Mean = 42.8049 StandardDev = 28.2922 WeightSum = 1080 Precision = Class normal: Prior probability = 0.5 0.13192612137203166 fly_identity_x_coverage: Normal Distribution. Mean = 14.1046 gene_region: Normal Distribution. Mean = 17.3128 StandardDev StandardDev = 22.1885 WeightSum = 1080 Precision = = 12.7019 WeightSum = 1080 Precision = 1.1833333333333333 0.2175824175824176 stain: Discrete Estimator. Counts = 1081 1 1 1 1 1 (Total = 1086) worm_identity_x_coverage: Normal Distribution. Mean = 11.5673 chips: Normal Distribution. Mean = 51.3093 StandardDev = StandardDev = 19.9173 WeightSum = 1080 Precision = 5.7113 WeightSum = 1080 Precision = 0.022233706720977596 0.2255125284738041 iep: Normal Distribution. Mean = 4.7248 StandardDev = 0.1978 drerio_identity_x_coverage: Normal Distribution. Mean = WeightSum = 1080 Precision = 0.0015156637168141592 36.6473 StandardDev = 28.479 WeightSum = 1080 Precision = family_size: Normal Distribution. Mean = 18.9983 StandardDev = 0.12853470437017994 73.4911 WeightSum = 1080 Precision = 11.738095238095237 dog_identity_x_coverage: Normal Distribution. Mean = 77.0888 exons: Normal Distribution. Mean = 8.7386 StandardDev = StandardDev = 23.1517 WeightSum = 1080 Precision = 8.9135 WeightSum = 1080 Precision = 4.597014925373134 0.2032520325203252 sigpep: Discrete Estimator. Counts = 912 170 (Total = 1082) bee_identity_x_coverage: Normal Distribution. Mean = 9.4907 transmembrane: Discrete Estimator. Counts = 835 247 (Total = StandardDev = 17.9179 WeightSum = 1080 Precision = 1082) 0.23349056603773585 gene_length: Normal Distribution. Mean = 45940.3638 drerio_identity: Normal Distribution. Mean = 44.2771 StandardDev = 90093.9458 WeightSum = 1080 Precision = StandardDev = 31.2632 WeightSum = 1080 Precision = 1000.0119502868068 1.2820512820512822 cdna_length: Normal Distribution. Mean = 2298.0112 dog_identity: Normal Distribution. Mean = 82.8067 StandardDev StandardDev = 1845.2476 WeightSum = 1080 Precision = = 20.1409 WeightSum = 1080 Precision = 1.5625 57.99126383226558 bee_identity: Normal Distribution. Mean = 14.5304 StandardDev residue_length: Normal Distribution. Mean = 476.1036 = 24.8419 WeightSum = 1080 Precision = 1.375 StandardDev = 472.1499 WeightSum = 1080 Precision = frog_identity: Normal Distribution. Mean = 55.5227 StandardDev 32.10088148873653 = 28.1115 WeightSum = 1080 Precision = 1.3157894736842106 gc: Normal Distribution. Mean = 46.8626 StandardDev = 8.4224 mouse_identity: Normal Distribution. Mean = 81.7993 WeightSum = 1080 Precision = 1.5555555555555556 StandardDev = 18.5808 WeightSum = 1080 Precision = len_3utr: Normal Distribution. Mean = 711.0701 StandardDev = 1.492537313432836 944.3569 WeightSum = 1080 Precision = 7.88860544217687 rat_identity: Normal Distribution. Mean = 78.7011 StandardDev = len_5utr: Normal Distribution. Mean = 158.3411 StandardDev = 23.279 WeightSum = 1080 Precision = 1.408450704225352 283.9746 WeightSum = 1080 Precision = 8.4348623853211 chicken_identity: Normal Distribution. Mean = 56.8654 a: Normal Distribution. Mean = 7.2078 StandardDev = 2.8889 StandardDev = 32.1139 WeightSum = 1080 Precision = WeightSum = 1080 Precision = 0.013338397328881469 1.3333333333333333 r: Normal Distribution. Mean = 5.8885 StandardDev = 2.7989 fugu_identity: Normal Distribution. Mean = 48.1447 StandardDev WeightSum = 1080 Precision = 0.023054755043227664 = 29.5 WeightSum = 1080 Precision = 1.25 n: Normal Distribution. Mean = 3.4037 StandardDev = 1.6835 frog_identity: Normal Distribution. Mean = 36.4547 StandardDev WeightSum = 1080 Precision = 0.006994470868014268 = 35.2097 WeightSum = 1080 Precision = 1.3157894736842106 d: Normal Distribution. Mean = 4.4132 StandardDev = 1.9705 mouse_identity: Normal Distribution. Mean = 62.7128 WeightSum = 1080 Precision = 0.011417650496785505 StandardDev = 37.9537 WeightSum = 1080 Precision = c: Normal Distribution. Mean = 2.5204 StandardDev = 2.0915 1.492537313432836 WeightSum = 1080 Precision = 0.020201417128773876 rat_identity: Normal Distribution. Mean = 59.1028 StandardDev = q: Normal Distribution. Mean = 4.4505 StandardDev = 1.9351 39.4827 WeightSum = 1080 Precision = 1.408450704225352 WeightSum = 1080 Precision = 0.011222980997624704 chicken_identity: Normal Distribution. Mean = 40.363 e: Normal Distribution. Mean = 6.5237 StandardDev = 2.9503 StandardDev = 38.1991 WeightSum = 1080 Precision = WeightSum = 1080 Precision = 0.020908027133973998 1.3333333333333333 g: Normal Distribution. Mean = 6.8172 StandardDev = 3.0996 fugu_identity: Normal Distribution. Mean = 31.6389 StandardDev WeightSum = 1080 Precision = 0.017684966216216215 = 33.3428 WeightSum = 1080 Precision = 1.25 h: Normal Distribution. Mean = 2.7115 StandardDev = 1.8014 fly_identity: Normal Distribution. Mean = 11.3813 StandardDev = WeightSum = 1080 Precision = 0.01905213622291022 21.4022 WeightSum = 1080 Precision = 1.434782608695652 i: Normal Distribution. Mean = 4.3795 StandardDev = 2.2797 worm_identity: Normal Distribution. Mean = 8.6079 StandardDev WeightSum = 1080 Precision = 0.010016030092592594 = 18.1673 WeightSum = 1080 Precision = 1.5714285714285714 l: Normal Distribution. Mean = 9.9368 StandardDev = 3.0421 mosquito_identity: Normal Distribution. Mean = 11.3313 WeightSum = 1080 Precision = 0.01193805260212647 StandardDev = 21.7775 WeightSum = 1080 Precision = k: Normal Distribution. Mean = 5.8537 StandardDev = 3.3076 1.4142857142857144 WeightSum = 1080 Precision = 0.015546918378678512 tetraodon_identity: Normal Distribution. Mean = 33.4081 m: Normal Distribution. Mean = 2.3535 StandardDev = 1.2692 StandardDev = 33.2262 WeightSum = 1080 Precision = WeightSum = 1080 Precision = 0.0076045627376425855 1.2820512820512822 f: Normal Distribution. Mean = 3.9442 StandardDev = 2.1656 mouse_dnds: Normal Distribution. Mean = 0.1426 StandardDev = WeightSum = 1080 Precision = 0.019527416520210897 0.1453 WeightSum = 749 Precision = 9.242306544202066E-4 p: Normal Distribution. Mean = 6.2626 StandardDev = 3.3575 mouse_dn: Normal Distribution. Mean = 0.0901 StandardDev = WeightSum = 1080 Precision = 0.023772330911123532 0.0969 WeightSum = 749 Precision = 6.754816112084063E-4 s: Normal Distribution. Mean = 7.9969 StandardDev = 2.9349 mouse_ds: Normal Distribution. Mean = 0.6252 StandardDev = WeightSum = 1080 Precision = 0.022804775280898876 0.2223 WeightSum = 749 Precision = 7.490019317450097E-4 t: Normal Distribution. Mean = 5.2103 StandardDev = 1.8306 rat_dnds: Normal Distribution. Mean = 0.1385 StandardDev = WeightSum = 1080 Precision = 0.01249046762589928 0.1382 WeightSum = 698 Precision = 7.33667564259486E-4 w: Normal Distribution. Mean = 1.3814 StandardDev = 1.0829 paralog_identity_x_coverage: Normal Distribution. Mean = 0 WeightSum = 1080 Precision = 0.006006487406398911 StandardDev = 0.0017 WeightSum = 1080 Precision = 0.01 y: Normal Distribution. Mean = 2.7441 StandardDev = 1.5341 paralog_identity: Normal Distribution. Mean = 0 StandardDev = WeightSum = 1080 Precision = 0.00726216049382716 0.0017 WeightSum = 1080 Precision = 0.01 v: Normal Distribution. Mean = 6 StandardDev = 2.0506 mouse_upstreams: Normal Distribution. Mean = 879.9005 WeightSum = 1080 Precision = 0.010865994236311238 StandardDev = 1150.4557 WeightSum = 851 Precision = mouse_identity_x_coverage: Normal Distribution. Mean = 10.021350407450525 57.8966 StandardDev = 37.2121 WeightSum = 1080 Precision = rat_upstreams: Normal Distribution. Mean = 857.5903 0.20833333333333334 StandardDev = 1147.1768 WeightSum = 846 Precision = rat_identity_x_coverage: Normal Distribution. Mean = 52.6352 10.307165871121716 StandardDev = 38.1794 WeightSum = 1080 Precision = chicken_upstreams: Normal Distribution. Mean = 358.3803 0.17421602787456447 StandardDev = 364.7584 WeightSum = 278 Precision = chicken_identity_x_coverage: Normal Distribution. Mean = 6.690600000000001 35.6264 StandardDev = 35.5667 WeightSum = 1080 Precision = 0.13297872340425532 fugu_identity_x_coverage: Normal Distribution. Mean = 27.673 Time taken to build model: 0.19 seconds StandardDev = 30.8553 WeightSum = 1080 Precision = 0.13192612137203166 === Evaluation on test set === fly_identity_x_coverage: Normal Distribution. Mean = 9.5178 === Summary === StandardDev = 18.8347 WeightSum = 1080 Precision = 0.2175824175824176 Correctly Classified Instances 1412 65.3704 % worm_identity_x_coverage: Normal Distribution. Mean = 6.832 Incorrectly Classified Instances 748 34.6296 % StandardDev = 15.3058 WeightSum = 1080 Precision = Kappa statistic 0.3074 0.2255125284738041 Mean absolute error 0.3469 drerio_identity_x_coverage: Normal Distribution. Mean = Root mean squared error 0.5664 24.7588 StandardDev = 29.5664 WeightSum = 1080 Precision = Relative absolute error 69.3813 % 0.12853470437017994 Root relative squared error 113.2889 % dog_identity_x_coverage: Normal Distribution. Mean = 59.3744 Total Number of Instances 2160 StandardDev = 38.0835 WeightSum = 1080 Precision = 0.2032520325203252 === Detailed Accuracy By Class === bee_identity_x_coverage: Normal Distribution. Mean = 6.4865 StandardDev = 15.7689 WeightSum = 1080 Precision = TP Rate FP Rate Precision Recall F-Measure Class 0.23349056603773585 0.775 0.468 0.624 0.775 0.691 disease drerio_identity: Normal Distribution. Mean = 30.1994 0.532 0.225 0.703 0.532 0.606 normal StandardDev = 33.3988 WeightSum = 1080 Precision = 1.2820512820512822 === Confusion Matrix === dog_identity: Normal Distribution. Mean = 63.2769 StandardDev = 39.2056 WeightSum = 1080 Precision = 1.5625 a b <-- classified as bee_identity: Normal Distribution. Mean = 10.2412 StandardDev 837 243 | a = disease = 22.1739 WeightSum = 1080 Precision = 1.375 505 575 | b = normal HGMD === Evaluation on test set ======Summary ===

Correctly Classified Instances 851 59.6774 % Incorrectly Classified Instances 575 40.3226 % Kappa statistic 0.1935 Mean absolute error 0.4039 Root mean squared error 0.6106 Relative absolute error 80.7869 % Root relative squared error 122.1272 % Total Number of Instances 1426

=== Detailed Accuracy By Class ===

TP Rate FP Rate Precision Recall F-Measure Class 0.668 0.474 0.585 0.668 0.623 disease 0.526 0.332 0.613 0.526 0.566 normal

=== Confusion Matrix ===

a b <-- classified as 476 237 | a = disease 338 375 | b = normal

POCUS === Evaluation on test set ======Summary ===

Correctly Classified Instances 73 73 % Incorrectly Classified Instances 27 27 % Kappa statistic 0.46 Mean absolute error 0.2706 Root mean squared error 0.5041 Relative absolute error 54.1149 % Root relative squared error 100.8194 % Total Number of Instances 100

=== Detailed Accuracy By Class ===

TP Rate FP Rate Precision Recall F-Measure Class 0.82 0.36 0.695 0.82 0.752 disease 0.64 0.18 0.78 0.64 0.703 normal

=== Confusion Matrix ===

a b <-- classified as 41 9 | a = disease 18 32 | b = normal

SELF_REDUCED === Run information === exons sigpep Scheme: weka.classifiers.bayes.NaiveBayes transmembrane Relation: training-weka.filters.unsupervised.attribute.Remove- gene_length R1-5,15-47,50-52,54-60,62-64 cdna_length Instances: 2160 residue_length Attributes: 14 gc len_3utr transmembrane: Discrete Estimator. Counts = 835 247 (Total = len_5utr 1082) mouse_identity gene_length: Normal Distribution. Mean = 45940.3638 rat_identity StandardDev = 90093.9458 WeightSum = 1080 Precision = worm_identity 1000.0119502868068 paralog_identity cdna_length: Normal Distribution. Mean = 2298.0112 phenotype StandardDev = 1845.2476 WeightSum = 1080 Precision = Test mode: user supplied test set: 2160 instances 57.99126383226558 residue_length: Normal Distribution. Mean = 476.1036 === Classifier model (full training set) === StandardDev = 472.1499 WeightSum = 1080 Precision = 32.10088148873653 Naive Bayes Classifier gc: Normal Distribution. Mean = 46.8626 StandardDev = 8.4224 WeightSum = 1080 Precision = 1.5555555555555556 Class disease: Prior probability = 0.5 len_3utr: Normal Distribution. Mean = 711.0701 StandardDev = 944.3569 WeightSum = 1080 Precision = 7.88860544217687 exons: Normal Distribution. Mean = 14.3018 StandardDev = len_5utr: Normal Distribution. Mean = 158.3411 StandardDev = 15.778 WeightSum = 1080 Precision = 4.597014925373134 283.9746 WeightSum = 1080 Precision = 8.4348623853211 sigpep: Discrete Estimator. Counts = 695 387 (Total = 1082) mouse_identity: Normal Distribution. Mean = 62.7128 transmembrane: Discrete Estimator. Counts = 770 312 (Total = StandardDev = 37.9537 WeightSum = 1080 Precision = 1082) 1.492537313432836 gene_length: Normal Distribution. Mean = 68736.0066 rat_identity: Normal Distribution. Mean = 59.1028 StandardDev = StandardDev = 138185.4067 WeightSum = 1080 Precision = 39.4827 WeightSum = 1080 Precision = 1.408450704225352 1000.0119502868068 worm_identity: Normal Distribution. Mean = 8.6079 StandardDev cdna_length: Normal Distribution. Mean = 3151.1808 = 18.1673 WeightSum = 1080 Precision = 1.5714285714285714 StandardDev = 3740.5714 WeightSum = 1080 Precision = paralog_identity: Normal Distribution. Mean = 0 StandardDev = 57.99126383226558 0.0017 WeightSum = 1080 Precision = 0.01 residue_length: Normal Distribution. Mean = 713.4124 StandardDev = 1173.8511 WeightSum = 1080 Precision = 32.10088148873653 Time taken to build model: 0.03 seconds gc: Normal Distribution. Mean = 46.6465 StandardDev = 8.3407 WeightSum = 1080 Precision = 1.5555555555555556 === Evaluation on test set === len_3utr: Normal Distribution. Mean = 830.5971 StandardDev = === Summary === 1042.2274 WeightSum = 1080 Precision = 7.88860544217687 len_5utr: Normal Distribution. Mean = 178.3895 StandardDev = Correctly Classified Instances 1267 58.6574 % 272.2791 WeightSum = 1080 Precision = 8.4348623853211 Incorrectly Classified Instances 893 41.3426 % mouse_identity: Normal Distribution. Mean = 81.7993 Kappa statistic 0.1731 StandardDev = 18.5808 WeightSum = 1080 Precision = Mean absolute error 0.411 1.492537313432836 Root mean squared error 0.5401 rat_identity: Normal Distribution. Mean = 78.7011 StandardDev = Relative absolute error 82.2096 % 23.279 WeightSum = 1080 Precision = 1.408450704225352 Root relative squared error 108.0237 % worm_identity: Normal Distribution. Mean = 13.7456 Total Number of Instances 2160 StandardDev = 22.4936 WeightSum = 1080 Precision = 1.5714285714285714 === Detailed Accuracy By Class === paralog_identity: Normal Distribution. Mean = 0 StandardDev = 0.0017 WeightSum = 1080 Precision = 0.01 TP Rate FP Rate Precision Recall F-Measure Class 0.364 0.191 0.656 0.364 0.468 disease 0.809 0.636 0.56 0.809 0.662 normal Class normal: Prior probability = 0.5 === Confusion Matrix === exons: Normal Distribution. Mean = 8.7386 StandardDev = 8.9135 WeightSum = 1080 Precision = 4.597014925373134 a b <-- classified as sigpep: Discrete Estimator. Counts = 912 170 (Total = 1082) 393 687 | a = disease 206 874 | b = normal

HGMD_REDUCED === Evaluation on test set ======Summary ===

Correctly Classified Instances 785 55.0491 % Incorrectly Classified Instances 641 44.9509 % Kappa statistic 0.101 Mean absolute error 0.4445 Root mean squared error 0.567 Relative absolute error 88.9047 % Root relative squared error 113.4099 % Total Number of Instances 1426 === Detailed Accuracy By Class ===

TP Rate FP Rate Precision Recall F-Measure Class 0.292 0.191 0.605 0.292 0.394 disease 0.809 0.708 0.533 0.809 0.643 normal

=== Confusion Matrix ===

a b <-- classified as 208 505 | a = disease 136 577 | b = normal

POCUS_REDUCED === Evaluation on test set ======Summary ===

Correctly Classified Instances 61 61 % Incorrectly Classified Instances 39 39 % Kappa statistic 0.22 Mean absolute error 0.3815 Root mean squared error 0.5092 Relative absolute error 76.2983 % Root relative squared error 101.8362 % Total Number of Instances 100

=== Detailed Accuracy By Class ===

TP Rate FP Rate Precision Recall F-Measure Class 0.46 0.24 0.657 0.46 0.541 disease 0.76 0.54 0.585 0.76 0.661 normal

=== Confusion Matrix ===

a b <-- classified as 23 27 | a = disease 12 38 | b = normal IBk IB1 instance-based classifier using 5 nearest neighbour(s) for classification

SELF === Evaluation on test set ======Summary ===

Correctly Classified Instances 1629 75.4167 % Incorrectly Classified Instances 531 24.5833 % Kappa statistic 0.5083 Mean absolute error 0.3174 Root mean squared error 0.4027 Relative absolute error 63.4882 % Root relative squared error 80.5349 % Total Number of Instances 2160

=== Detailed Accuracy By Class ===

TP Rate FP Rate Precision Recall F-Measure Class 0.785 0.277 0.739 0.785 0.762 disease 0.723 0.215 0.771 0.723 0.746 normal

=== Confusion Matrix ===

a b <-- classified as 848 232 | a = disease 299 781 | b = normal

HGMD

=== Evaluation on test set ======Summary ===

Correctly Classified Instances 907 63.6045 % Incorrectly Classified Instances 519 36.3955 % Kappa statistic 0.2721 Mean absolute error 0.4055 Root mean squared error 0.4933 Relative absolute error 81.0975 % Root relative squared error 98.6669 % Total Number of Instances 1426

=== Detailed Accuracy By Class ===

TP Rate FP Rate Precision Recall F-Measure Class 0.68 0.408 0.625 0.68 0.651 disease 0.592 0.32 0.649 0.592 0.619 normal

=== Confusion Matrix ===

a b <-- classified as 485 228 | a = disease 291 422 | b = normal

POCUS

=== Evaluation on test set ======Summary === Correctly Classified Instances 73 73 % Incorrectly Classified Instances 27 27 % Kappa statistic 0.46 Mean absolute error 0.356 Root mean squared error 0.4481 Relative absolute error 71.2053 % Root relative squared error 89.6195 % Total Number of Instances 100

=== Detailed Accuracy By Class ===

TP Rate FP Rate Precision Recall F-Measure Class 0.76 0.3 0.717 0.76 0.738 disease 0.7 0.24 0.745 0.7 0.722 normal

=== Confusion Matrix ===

a b <-- classified as 38 12 | a = disease 15 35 | b = normal

SELF_REDUCED === Evaluation on test set ======Summary ===

Correctly Classified Instances 1622 75.0926 % Incorrectly Classified Instances 538 24.9074 % Kappa statistic 0.5019 Mean absolute error 0.3241 Root mean squared error 0.4041 Relative absolute error 64.816 % Root relative squared error 80.8124 % Total Number of Instances 2160

=== Detailed Accuracy By Class ===

TP Rate FP Rate Precision Recall F-Measure Class 0.791 0.289 0.732 0.791 0.76 disease 0.711 0.209 0.773 0.711 0.741 normal

=== Confusion Matrix ===

a b <-- classified as 854 226 | a = disease 312 768 | b = normal

HGMD_REDUCED === Evaluation on test set ======Summary ===

Correctly Classified Instances 889 62.3422 % Incorrectly Classified Instances 537 37.6578 % Kappa statistic 0.2468 Mean absolute error 0.4054 Root mean squared error 0.4933 Relative absolute error 81.0701 % Root relative squared error 98.6535 % Total Number of Instances 1426

=== Detailed Accuracy By Class ===

TP Rate FP Rate Precision Recall F-Measure Class 0.661 0.414 0.615 0.661 0.637 disease 0.586 0.339 0.633 0.586 0.609 normal === Confusion Matrix ===

a b <-- classified as 471 242 | a = disease 295 418 | b = normal

POCUS_REDUCED === Evaluation on test set ======Summary ===

Correctly Classified Instances 59 59 % Incorrectly Classified Instances 41 41 % Kappa statistic 0.18 Mean absolute error 0.3997 Root mean squared error 0.4871 Relative absolute error 79.9466 % Root relative squared error 97.4169 % Total Number of Instances 100

=== Detailed Accuracy By Class ===

TP Rate FP Rate Precision Recall F-Measure Class 0.54 0.36 0.6 0.54 0.568 disease 0.64 0.46 0.582 0.64 0.61 normal

=== Confusion Matrix ===

a b <-- classified as 27 23 | a = disease 18 32 | b = normal PART

SELF === Run information === mouse_dn mouse_ds Scheme: weka.classifiers.rules.PART -M 2 -C 0.25 -Q 1 rat_dnds Relation: training paralog_identity_x_coverage Instances: 2160 paralog_identity Attributes: 65 mouse_upstreams gene_region rat_upstreams stain chicken_upstreams chips phenotype iep Test mode: user supplied test set: 2160 instances family_size exons === Classifier model (full training set) === sigpep transmembrane PART decision list gene_length ------cdna_length residue_length mouse_identity <= 37 AND gc fugu_identity_x_coverage <= 20.21 AND len_3utr frog_identity <= 25 AND len_5utr exons <= 3: normal (167.0) a r family_size > 47 AND n transmembrane = 1: normal (18.0) d c dog_identity <= 40 AND q mouse_identity_x_coverage <= 25.22 AND e fugu_identity_x_coverage <= 24.15 AND g frog_identity <= 47 AND h e > 2.18182: normal (70.0) i l sigpep = 1 AND k residue_length > 391 AND m mouse_identity <= 91 AND f n > 4.34363 AND p family_size > 3: disease (65.0) s t exons > 31 AND w rat_identity_x_coverage > 45.59 AND y m <= 2.03252: disease (41.0) v mouse_identity_x_coverage worm_identity > 58 AND rat_identity_x_coverage r <= 8.39695 AND chicken_identity_x_coverage dog_identity_x_coverage <= 91.2: disease (36.0/1.0) fugu_identity_x_coverage fly_identity_x_coverage sigpep = 1 AND worm_identity_x_coverage rat_identity <= 93 AND drerio_identity_x_coverage family_size <= 19 AND dog_identity_x_coverage tetraodon_identity > 0 AND bee_identity_x_coverage transmembrane = 0 AND drerio_identity exons > 4 AND dog_identity p <= 5.88235 AND bee_identity chicken_identity <= 79 AND frog_identity iep <= 4.7221: disease (35.0) mouse_identity rat_identity r > 8.58283 AND chicken_identity sigpep = 0 AND fugu_identity w <= 0.31348: normal (17.0) fly_identity worm_identity sigpep = 1 AND mosquito_identity family_size <= 17 AND tetraodon_identity rat_identity <= 93 AND mouse_dnds exons > 23 AND mouse_ds <= 0.8843: disease (20.0) h > 4.4335 AND transmembrane = 0: disease (15.0) fugu_identity > 42 AND family_size > 2 AND family_size <= 2 AND mouse_dn > 0.0081 AND sigpep = 0 AND n > 2.64706 AND family_size > 1 AND transmembrane = 1 AND gc > 52 AND sigpep = 0 AND d <= 4.25532: normal (22.0) y > 2.44898 AND chicken_identity_x_coverage <= 72.25: disease (33.85) family_size <= 2 AND sigpep = 0 AND sigpep = 1 AND transmembrane = 0 AND mouse_identity <= 91 AND mouse_dnds > 0.272677 AND fugu_identity_x_coverage > 46.08 AND p > 4.5977 AND drerio_identity <= 71 AND f > 1.1976: normal (31.5/0.4) f > 4.31655: disease (41.0) g <= 6.33894 AND mosquito_identity > 51 AND family_size > 22 AND bee_identity > 76 AND w <= 2.69461: normal (25.0) bee_identity_x_coverage > 28 AND rat_dnds <= 0.028325: normal (14.57) family_size > 24 AND rat_upstreams > 110.16 AND mosquito_identity > 51 AND a <= 8.4922: disease (30.52/2.0) sigpep = 0 AND mosquito_identity > 70 AND fly_identity > 30 AND f <= 5.24272: disease (32.14/1.14) chicken_identity_x_coverage > 60 AND fly_identity > 34 AND mosquito_identity > 51 AND gene_region > 6 AND chicken_identity <= 91 AND frog_identity > 58 AND sigpep = 0 AND transmembrane = 0 AND transmembrane = 0 AND e > 6.06061 AND e <= 8.08081 AND sigpep = 0 AND e > 4.41426 AND chicken_identity > 80 AND w > 0.616197 AND rat_identity_x_coverage <= 90.16: normal (23.9) len_3utr <= 1536 AND m <= 3.43348: disease (57.0) family_size > 2 AND mouse_identity > 97 AND sigpep = 1 AND gc <= 55 AND transmembrane = 0 AND exons <= 13 AND exons > 16 AND mouse_upstreams <= 755.37: normal (18.45) cdna_length > 2782: normal (9.0) family_size > 2 AND sigpep = 1 AND rat_identity <= 60 AND transmembrane = 0 AND bee_identity_x_coverage <= 25.2 AND m > 2.20859 AND gene_length <= 5981 AND k <= 7.22892: disease (44.0/3.0) n <= 4.57627: disease (10.0) rat_identity_x_coverage <= 57.42 AND rat_identity <= 43 AND sigpep = 0 AND bee_identity <= 41 AND frog_identity <= 47 AND rat_dnds <= 0.634978 AND worm_identity <= 27 AND sigpep = 0 AND dog_identity > 73: normal (51.29/1.0) transmembrane = 0 AND bee_identity_x_coverage <= 6.96 AND sigpep = 1 AND r <= 8.01457: normal (15.45/3.0) exons > 12 AND g <= 10.7143 AND family_size > 2 AND exons <= 14: disease (17.0/1.0) rat_identity <= 60 AND bee_identity_x_coverage <= 25.2 AND frog_identity <= 49 AND drerio_identity_x_coverage <= 76.63 AND len_5utr <= 6 AND exons <= 9 AND drerio_identity <= 59 AND n > 4.51866: normal (15.0/0.5) sigpep = 0: normal (54.0/5.0) family_size > 2 AND family_size <= 2 AND m > 1.88356 AND cdna_length > 7035 AND sigpep = 0 AND mouse_ds > 0.4515: disease (15.63) transmembrane = 0 AND gc > 42 AND family_size <= 2 AND rat_upstreams <= 3706.76 AND sigpep = 0 AND v <= 5.2223 AND family_size > 1 AND iep <= 4.899: disease (40.93/1.0) mosquito_identity <= 29 AND transmembrane = 1 AND rat_identity_x_coverage > 30.78 AND residue_length <= 225 AND fly_identity_x_coverage <= 12.06 AND f > 3.31492 AND k <= 9.28382 AND exons > 4: normal (20.0) chips <= 57.658 AND a > 8.75: normal (11.0) transmembrane = 1 AND worm_identity > 30 AND sigpep = 1 AND mosquito_identity <= 35 AND rat_identity_x_coverage > 18.48 AND sigpep = 0 AND len_5utr > 169: disease (11.0) d <= 4.17827: normal (14.0) sigpep = 1 AND transmembrane = 1 AND len_3utr <= 281: normal (13.0/1.0) sigpep = 0 AND mouse_identity_x_coverage <= 51.6 AND sigpep = 1 AND len_3utr <= 899: normal (10.0) d <= 6.11205 AND rat_identity_x_coverage <= 93: disease (10.0) transmembrane = 1 AND sigpep = 0 AND sigpep = 0 AND gene_region <= 31 AND dog_identity_x_coverage > 98 AND exons > 20 AND gc <= 56 AND len_5utr <= 312: disease (20.0/1.0) gene_length <= 30631: normal (18.28) transmembrane = 1 AND sigpep = 0: disease (619.98/305.33) sigpep = 0 AND gene_region <= 31 AND : normal (5.0) rat_identity > 93 AND a <= 8.87574 AND Number of Rules : 48 rat_identity_x_coverage <= 95.06: disease (15.15) transmembrane = 1 AND Time taken to build model: 9.67 seconds g <= 4.53333 AND n <= 5.01792: normal (19.0/1.0) === Evaluation on test set ======Summary === transmembrane = 1: disease (250.0/102.0) Correctly Classified Instances 1744 80.7407 % sigpep = 1 AND Incorrectly Classified Instances 416 19.2593 % r <= 4.0201 AND Kappa statistic 0.6148 len_5utr <= 225: disease (16.38) Mean absolute error 0.2182 Root mean squared error 0.3294 sigpep = 1 AND Relative absolute error 43.6357 % exons > 6 AND Root relative squared error 65.879 % m > 1.53453: normal (12.0) Total Number of Instances 2160 sigpep = 1 AND === Detailed Accuracy By Class === worm_identity_x_coverage <= 26.6 AND mosquito_identity <= 29 AND TP Rate FP Rate Precision Recall F-Measure Class family_size <= 16 AND 0.983 0.369 0.727 0.983 0.836 disease gene_region <= 30 AND 0.631 0.017 0.974 0.631 0.766 normal c <= 6.30252 AND fly_identity_x_coverage <= 12.06 AND === Confusion Matrix === l > 14.8746: disease (9.0) a b <-- classified as sigpep = 1 AND 1062 18 | a = disease worm_identity_x_coverage <= 26.6 AND 398 682 | b = normal

HGMD === Summary ===

Correctly Classified Instances 894 62.6928 % Incorrectly Classified Instances 532 37.3072 % Kappa statistic 0.2539 Mean absolute error 0.3823 Root mean squared error 0.5098 Relative absolute error 76.4605 % Root relative squared error 101.9583 % Total Number of Instances 1426 === Detailed Accuracy By Class ===

TP Rate FP Rate Precision Recall F-Measure Class 0.802 0.548 0.594 0.802 0.683 disease 0.452 0.198 0.695 0.452 0.548 normal

=== Confusion Matrix ===

a b <-- classified as 572 141 | a = disease 391 322 | b = normal

POCUS === Evaluation on test set ======Summary ===

Correctly Classified Instances 69 69 % Incorrectly Classified Instances 31 31 % Kappa statistic 0.38 Mean absolute error 0.3705 Root mean squared error 0.4865 Relative absolute error 74.1091 % Root relative squared error 97.2977 % Total Number of Instances 100

=== Detailed Accuracy By Class ===

TP Rate FP Rate Precision Recall F-Measure Class 0.84 0.46 0.646 0.84 0.73 disease 0.54 0.16 0.771 0.54 0.635 normal

=== Confusion Matrix ===

a b <-- classified as 42 8 | a = disease 23 27 | b = normal

SELF_REDUCED === Run information === PART decision list ------Scheme: weka.classifiers.rules.PART -M 2 -C 0.25 -Q 1 Relation: training-weka.filters.unsupervised.attribute.Remove- mouse_identity <= 37 AND R1-5,15-47,50-52,54-60,62-64 sigpep = 0 AND Instances: 2160 rat_identity <= 80 AND Attributes: 14 exons <= 2: normal (132.0) exons sigpep mouse_identity <= 54 AND transmembrane sigpep = 0 AND gene_length rat_identity <= 80: normal (144.0/15.0) cdna_length residue_length gene_length <= 992 AND gc transmembrane = 1: normal (32.0/1.0) len_3utr len_5utr exons > 31 AND mouse_identity sigpep = 1: disease (41.0/2.0) rat_identity worm_identity sigpep = 1 AND paralog_identity rat_identity > 43 AND phenotype rat_identity <= 93 AND Test mode: user supplied test set: 2160 instances cdna_length > 1510 AND mouse_identity <= 91: disease (247.0/37.0) === Classifier model (full training set) === exons > 31 AND transmembrane = 0 AND transmembrane = 0: normal (37.0/10.0) gene_length <= 91520: disease (20.0/1.0) sigpep = 1 AND worm_identity > 45 AND mouse_identity <= 0: normal (11.0) rat_identity <= 97 AND worm_identity > 60 AND transmembrane = 0 AND transmembrane = 0 AND sigpep = 0: disease (883.0/419.0) exons > 11: disease (31.0) worm_identity > 30 AND mouse_identity <= 76 AND sigpep = 1 AND sigpep = 0 AND len_3utr <= 371: normal (7.0) gc <= 43 AND exons <= 14 AND worm_identity > 30 AND transmembrane = 0: normal (63.0/10.0) sigpep = 0 AND exons > 4 AND residue_length <= 244 AND residue_length <= 420: normal (14.0) sigpep = 0 AND exons <= 2: normal (35.0/6.0) transmembrane = 1 AND sigpep = 0: disease (173.0/81.0) transmembrane = 1 AND exons > 19 AND len_5utr <= 402 AND sigpep = 0 AND transmembrane = 1 AND mouse_identity > 74: disease (40.0/4.0) worm_identity <= 0: disease (60.0/24.0) transmembrane = 0 AND len_5utr > 135: normal (12.0) sigpep = 1 AND mouse_identity > 61: disease (83.0/25.0) worm_identity <= 25 AND residue_length <= 263: disease (6.0/1.0) rat_identity <= 37 AND worm_identity <= 27 AND worm_identity <= 25: normal (6.0/1.0) transmembrane = 0 AND sigpep = 1 AND : disease (3.0) residue_length <= 354: normal (15.0) Number of Rules : 27 worm_identity > 45 AND transmembrane = 1 AND sigpep = 0 AND Time taken to build model: 0.8 seconds gc > 38 AND residue_length > 288: disease (12.0) === Evaluation on test set ======Summary === transmembrane = 1 AND sigpep = 1 AND Correctly Classified Instances 1514 70.0926 % exons > 12 AND Incorrectly Classified Instances 646 29.9074 % gene_length > 33341: disease (29.0/7.0) Kappa statistic 0.4019 Mean absolute error 0.349 sigpep = 1 AND Root mean squared error 0.4177 transmembrane = 0 AND Relative absolute error 69.8009 % mouse_identity <= 44: disease (10.0/1.0) Root relative squared error 83.5469 % Total Number of Instances 2160 sigpep = 1 AND mouse_identity > 0 AND === Detailed Accuracy By Class === len_5utr <= 398 AND len_5utr <= 9 AND TP Rate FP Rate Precision Recall F-Measure Class transmembrane = 1 AND 0.959 0.557 0.632 0.959 0.762 disease mouse_identity > 67: normal (14.0/1.0) 0.443 0.041 0.916 0.443 0.597 normal rat_identity <= 51 AND === Confusion Matrix === worm_identity <= 34 AND worm_identity <= 0 AND a b <-- classified as sigpep = 0 AND 1036 44 | a = disease rat_identity <= 0 AND 602 478 | b = normal

HGMD_REDUCED === Evaluation on test set ======Summary ===

Correctly Classified Instances 891 62.4825 % Incorrectly Classified Instances 535 37.5175 % Kappa statistic 0.2496 Mean absolute error 0.4121 Root mean squared error 0.4812 Relative absolute error 82.4288 % Root relative squared error 96.233 % Total Number of Instances 1426

=== Detailed Accuracy By Class ===

TP Rate FP Rate Precision Recall F-Measure Class 0.889 0.64 0.582 0.889 0.703 disease 0.36 0.111 0.765 0.36 0.49 normal

=== Confusion Matrix ===

a b <-- classified as 634 79 | a = disease 456 257 | b = normal

POCUS_REDUCED === Evaluation on test set ======Summary ===

Correctly Classified Instances 64 64 % Incorrectly Classified Instances 36 36 % Kappa statistic 0.28 Mean absolute error 0.3864 Root mean squared error 0.4501 Relative absolute error 77.275 % Root relative squared error 90.0147 % Total Number of Instances 100

=== Detailed Accuracy By Class ===

TP Rate FP Rate Precision Recall F-Measure Class 0.96 0.68 0.585 0.96 0.727 disease 0.32 0.04 0.889 0.32 0.471 normal

=== Confusion Matrix ===

a b <-- classified as 48 2 | a = disease 34 16 | b = normal