PBC4cip manual

Installation

Open Weka's Package manager (Tools > Package manager). Select File/URL from the Package manager and select the PBC4cip package to install it. After installing the package, you need to close and open Weka before using it.

PBC4cip parameters

PBC4cip has only two parameters: miner and filter. The miner extracts contrast patterns (CPs), right now the only working miner is RandomForestMinerWithoutFiltering. If the filter parameter is set to true, the patterns are filtered, keeping only the most general.


Since PBC4cip implements Weka's RandomizableClassifier interface, the classification results will only change if you change the seed.

Random forest miner

The miner extracts CPs from a random forest of trees built using the selected builder. There are two builders implemented: 

The number of trees is set with numTrees

If bagging is set to True, each tree is built using random samples with replacement from the training dataset. The number of samples is a percentage of the original size of the dataset, specified with bagSizePercent.

The numFeatures parameter sets the number of randomly selected features used to build each tree; if the parameter is set to -1, log2(features)+1 are randomly selected 

Decision tree builders

The following parameters are common to the univariate and multivariate decision tree builders:

The multivariate decision tree builder has two extra parameters: