Chameleon Features Categorical Variables Anomaly Detection Missing Values Prediction Feature Extraction Proprietary Algorithms Seventh Sense Software Chameleon Homepage Cluster Analysis Density Estimation Classification Visualisation


Chameleon Statistics is ideal for working with numerical data or images. Besides being an excellent general-purpose tool for clustering and classification, it will be especially valuable to anyone requiring outstanding quality graphical presentation of their data - whether that be for marketing to potential clients or for disseminating research results to peers. Chameleon Statistics Scientific Edition currently consists of the following major components:

Input Format(s): Datasets are lists of samples consisting of (numerical) feature vectors. Please see the FAQ for details about limitations on dataset size and related information.

Feature Selection: Principal components analysis, Variable weighting/masking.

Cluster Analysis: Hierarchical methods. Single-link method (nearest neighbour), Ward's method (sum of squares), Centroid method, Complete link (furthest neighbour), Group average method, Median method, Lance Williams (parametric).
Partitional methods. K-Means.

Density Estimation: Multivariate Gaussian, Kernel methods, k-Nearest neighbours, Enhanced k-nearest neighbours.

Classification: Each of the density methods above can be used for classification.

Visualisation: Fully configurable 2D/3D scatter plots, density plots and contour plots, histograms, binary trees/dendograms, rotations/animations, bitmap displays.

Click on the links above for more detailed descriptions of each component.

*PLANNED FOR FUTURE RELEASE: Chameleon Statistics Professional Edition is currently under development. This will include all essential features of the Scientific Edition, as well as the following additional components: Automated Feature Extraction, Missing Value Handling, Multivariate Imputation, Mixed Data Type Handling & Anomaly and Outlier Detection.