Stochastic Learning Toolkit.
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COPYING
COPYING.LESSER
Makefile
README.md
binary.cpp
common.h
data_set.cpp
data_set.h
learner.cpp
learner.h
learner_binary.cpp
learner_binary.h
learner_multiclass.cpp
learner_multiclass.h
learner_multilabel.cpp
learner_multilabel.h
model.cpp
model.h
multiclass.cpp
multilabel.cpp
sparse_data_format.cpp
sparse_data_format.h
sparse_data_format_test.cpp
sparse_vector.cpp
sparse_vector.h
weight_vector.cpp
weight_vector.h

README.md

Sol - Stochastic Learner

Copyright (C) 2011-2012 Heidelberg University

Author: Sascha Fendrich

Description

Sol implements several stochastic machine learning algorithms.

sol-bin - binary classification
sol-mucl - multi-class classification
sol-mulab - multi-label classification (small number of labels, only)

Input Format

  • Uses svmlight's sparse data format for input
  • For multi-class classification classes should be numbered from 0 to N-1
  • For multi-label classification the labels should be numbered from 0 to N-1 and correspond to the bits in the class number given in the training data. This will probably change in future versions.

Dependencies

  • STL
  • Boost program options
  • tiny_log logging library (directly imported as a git submodule)

Compilation

  • Clone the github repository:

    git clone https://github.com/sfendrich/sol.git
    
  • Register and fetch submodules:

    make submodules
    
  • Compile sol:

    make