Project details for NaN toolbox

Logo NaN toolbox 2.1.0

by schloegl - February 28, 2010, 22:00:21 CET [ Project Homepage BibTeX Download ]

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The NaN-toolbox provides a number of statistics functions and machine learning methods for the use with Octave and Matlab. The functions can handle data with missing values encoded as NaNs, weighting of data samples, and multi-class classification (using a one-versus-rest scheme). There is a common interface to a number of different classification methods (including FDA, LDA, Naive Bayes, QDA, RDA, sparse classifiers, interfaces to some SVMs, regression/PLS, Wiener-Hopf).

Changes to previous version:

-) Feature ranking algorithm added (fss.m) -) train_sc: {-1,+1}-encoding of classlabels supported weighted liblinear and svm source code included add "Deletion"-Mode: this enables NaN-support for training algorithms that did not have support for data with SVM (liblinear, SVM, etc.) -) str2double.mex for fast decoding of delimiter files. -) bug fixes (train_sc PLA)

Some minor bug fixes. For details see:

BibTeX Entry: Download
Supported Operating Systems: Agnostic
Data Formats: Matlab
Tags: Classification, Multi Class, Machine Learning, Missing Data, Statistics, Weighting
Archive: download here


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