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ChangeLog
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ChangeLog
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Version 0.4.2+
* Add select_n_best & rank_corr to featureselection
* Add Euclidean MDS
* Add tree multi-class strategy
Version 0.4.2 2012-01-16 by luispedro
* Make defaultlearner able to take extra arguments
* Make ctransforms_model a supervised_model (adds apply_many)
* Add expanded argument to defaultlearner
* Fix corner case in SDA
* Fix repeated_kmeans
* Fix parallel gridminimise on Windows
* Add multi_label argument to normaliselabels
* Add multi_label argument to nfoldcrossvalidation.foldgenerator
* Do not fork a process in gridminimise if nprocs == 1 (makes for easier
debugging, at the cost of slightly more complex code).
* Add milk.supervised.multi_label
* Fix ext.jugparallel when features is a Task
* Add milk.measures.bayesian_significance
Version 0.4.1 2011-08-25 by luispedro
* Fix important bug in multi-process gridsearch
Version 0.4.0 2011-08-24 by luispedro
* Use multiprocessing to take advantage of multi core machines (off by
default).
* Add perceptron learner
* Set random seed in random forest learner
* Add warning to milk/__init__.py if import fails
* Add return value to ``gridminimise``
* Set random seed in ``precluster_learner``
* Implemented Error-Correcting Output Codes for reduction of multi-class
to binary (including probability estimation)
* Add ``multi_strategy`` argument to ``defaultlearner()``
* Make the dot kernel in svm much, much, faster
* Make sigmoidal fitting for SVM probability estimates faster
* Fix bug in randomforest (patch by Wei on milk-users mailing list)
Version 0.3.10 2011-05-10 by luispedro
* Add ext.jugparallel
* parallel nfold crossvalidation using jug
* parallel multiple kmeans runs using jug
* cluster_agreement for non-ndarrays
* Add histogram & normali(z|s)e options to ``milk.kmeans.assign_centroid``
* Fix bug in sda when features were constant for a class
* Add select_best_kmeans
* Added defaultlearner as a better name than defaultclassifier
* Add `measures.curves.precision_recall`
* Add `unsupervised.parzen.parzen`
Version 0.3.9 2011-03-15 by luispedro
* Improve speed of k-nearest neighbour (10x on scikits-learn benchmark)
* Fix gridminize for low count labels
* Improve kmeans on newer numpy (works for larger datasets)
* Add ``folds`` argument to ``nfoldcrossvalidation``
* Add ``assign_centroid`` function in milk.unsupervised.nfoldcrossvalidation
* Faster kmeans by coding centroid recalculation in C++
* Fix bug with non-integer labels for tree learning
Version 0.3.8 2011-02-12 luispedro
* Fix compilation on Windows
Version 0.3.7 2011-02-10 luispedro
* Logistic regression
* Source demos included (in source and documentation)
* Add cluster agreement metrics
* Fix nfoldcrossvalidation bug when using origins
Version 0.3.6 2010-12-17 luispedro
* Unsupervised (1-class) kernel density modeling
* Fix for when SDA returns empty
* weights option to some learners
* stump learner
* Adaboost (result of above changes)
Version 0.3.5 2010-11-3
* Fixes for 64 bit machines.
* Functions in measures.py all have same interface now.
Version 0.3.4 2010-10-31
* Random forest learners
* Decision trees sped up 20x
* Much faster gridsearch (finds optimum without computing all folds)
Version 0.3.3 2010-10-22
* Missing file added to distribution
Version 0.3.2
* kmeans() for distance=mahalanobis
* minimise dependency on scipy
* self-organising maps
* important bug fix in repeated_kmeans
* faster feature selection
Version 0.3.1 2010-09-25
* fix sparse non-negative matrix factorisation
* mean grouped classifier
* update multi classifier to newer interface
Version 0.3 2010-09-23
* no scipy.weave dependency
* flatter namespace
* faster kmeans
* affinity propagation (borrowed from scikits-learn & slightly improved)
* pdist()