Contents

# 0.2.4
- Added class for Factorization Machine classifier.
- Added classes for evaluation measures.
- Fixed the method for prediction of class probability in Logistic Regression.

# 0.2.3
- Added class for cross validation.
- Added specs for base modules.
- Fixed validation of the number of splits when a negative label is given.

# 0.2.2
- Added data splitter classes for K-fold cross validation.

# 0.2.1
- Added class for K-nearest neighbors classifier.

# 0.2.0
- Migrated the linear algebra library to Numo::NArray.
- Added module for loading and saving libsvm format file.

# 0.1.3
- Added class for Kernel Support Vector Machine with Pegasos algorithm.
- Added module for calculating pairwise kernel fuctions and euclidean distances.

# 0.1.2
- Added the function learning a model with bias term to the PegasosSVC and LogisticRegression classes.
- Rewrited the document with yard notation.

# 0.1.1
- Added class for Logistic Regression with SGD optimization.
- Fixed some mistakes on the document.

# 0.1.0
- Added basic classes.
- Added an utility module.
- Added class for RBF kernel approximation.
- Added class for Support Vector Machine with Pegasos alogrithm.
- Added class that performs mutlclass classification with one-vs.-rest strategy.
- Added classes for preprocessing such as min-max scaling, standardization, and L2 normalization.

Version data entries

1 entries across 1 versions & 1 rubygems

Version	Path
svmkit-0.2.4	HISTORY.md