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ELKI
Effect of Distance Measures on Partitional Clustering Algorithms
BETULA: Numerically Stable CF-Trees for BIRCH Clustering?
Research Techniques in Network and Information Technologies, February
Machine Learning for Improved Data Analysis of Biological Aerosol Using the WIBS
Principal Component Analysis
A Study on Adoption of Data Mining Tools and Collision of Predictive Techniques
A Comparative Study on Various Data Mining Tools for Intrusion Detection
ELKI: ELKI: ELKI: a Software System for Evaluation a Software System
Spca Assisted Correlation Clustering of Hyperspectral Imagery
275: Robust Principal Component Analysis for Generalized Multi-View
Statistically Rigorous Testing of Clustering Implementations
Machine-Learning
ELKI: a Large Open-Source Library for Data Analysis
Survey and Performance Evaluation of DBSCAN Spatial Clustering Implementations for Big Data and High-Performance Computing Paradigms
Free and Open Source Software
Design and Development of a BANG-File Clustering System“
Big Data, Data Mining & Artificial Intelligence
A Generic Data Analysis Application
Top View
Local Outlier Detection with Interpretation⋆
Evaluation of Clusterings – Metrics and Visual Support
Package 'Dbscan'
Machine Learning for Improved Data Analysis of Biological Aerosol Using the WIBS Simon Ruske1, David O
ELKI 0.2 for the Performance Evaluation of Distance Measures for Time Series
Dbscan: Fast Density-Based Clustering with R
Scalable Kernel Density Estimation-Based Local Outlier Detection Over Large Data Streams∗
Dbscan: Fast Density-Based Clustering with R
On the Use of Social Trajectory-Based Clustering Methods for Public Transport Optimization
An Overview of Free Software Tools for General Data Mining
Local Outlier Detection with Interpretation
Paper Title (Use Style: Paper Title)
Machine Learning for Improved Data Analysis of Biological Aerosol Using the WIBS
3.1.2 Spectral Algorithm for Anomaly Detection
KDD-SC: Subspace Clustering Extensions for Knowledge Discovery Frameworks
D4.2. Measure
21 the Singular Value Decomposition; Clustering
A Comparison of Different R-Tree Construction Techniques for Range Queries on Neuromorphological Data