I have completed a small collection of libraries useful for machine learning and data mining. It requires win32, Python 2.1 and the Orange machine learning framework library, both freely downloadable.
Features: Clustering / Unsupervised Learning: - k-means (medoid) clustering - fuzzy clustering - hierarchical agglomerative clustering
Supervised Learning: - multiclass logistic regression - multiclass SVM for classification, regression, and density estimation - wrapped multiclass SVM classifier which outputs class probabilities - general wrappers for multiclass classification with binary classifiers - several ensemble construction methods - support for "merging" the final classification from ensembles of classifiers that output probability distributions
Note that Orange itself provides tremendously many features: discretization, k-NN, classification and regression trees, naive Bayes classifiers, evaluation techniques (stratified cross validation, random sampling, aROC, etc), constructive induction, etc. Check out http://magix.fri.uni-lj.si/orange/
It can all be found at http://ai.fri.uni-lj.si/%7Ealeks/orng/ I'm sorry for not supporting Python 2.2, and platforms other than win32 at the moment. But all that will come provided sufficient user stimulation.
Best regards, Aleks
Aleks Jakulin (jakulin@@ieee.org) Faculty of Computer and Information Science University of Ljubljana Slovenia +386 41 379 137