MIL learners and their ensemble versions
2016-08-23
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This toolbox contains programs for four different multi-instance learners and their ensemble versions. In detail, this toolbox contains three parts:
1)Data Preparation
This part includes three components:
1.1) Original Musk data [1] from UCI machine learning repository
1.2) Preprocessed Musk data for further usage
1.3) Functions for dividing the Musk data into 10 folds, which are called before conducting 10-fold cross-validation experiments
1.4) Function for performing min max normalization
2)Individual Algorithm<
1)Data Preparation
This part includes three components:
1.1) Original Musk data [1] from UCI machine learning repository
1.2) Preprocessed Musk data for further usage
1.3) Functions for dividing the Musk data into 10 folds, which are called before conducting 10-fold cross-validation experiments
1.4) Function for performing min max normalization
2)Individual Algorithm<
matlab
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