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# Diversified Multiple Decision Trees

## Introduction

This program uses diversified multiple decision trees to make high accurate predictions on high dimensional data sets. See explanations and experimental results in A Maximally Diversified Multiple Decision Tree Algorithm for Microarray Data Classification.

This software tool works on Windows. (embedded in Weka.)

## Get program

Download here

## Run program

Click run.bat to run the program.

Click Explorer at the GUI interface of Weka

Open amlall.arff file

Choose Classify -> Choose -> meta -> MDMT_J48

Set parameters as the following. You may click More to read explanations about options.

Click start to run and should get the following results

## Other options

eliminateAllAttributes: TRUE removes all attributes used by the previous tree, FALSE removes only the root node of the previous tree.

votingType: 0 unweighed vote of trees. 1 weighted by the confidence of the decision leaf. 2 weighted by the support of the decision leaf, 3 weighted by the Laplace accuracy of the decision leaf.

useDiversity = TRUE

A new tree has to satisfy the diversity requirement specified by minDiversity with all existing trees used by MDMT. Diversity is defined as the following.

Let errorSeti = the set of instances in the training data misclassified by treei Let errorSetj = the set of instances in the training data misclassified by treej
Diversity = 1 - |errorSeti intersection errorSetj| / |errorSeti union errorSetj| |

If a new tree does not satisfy the minimum diversity requirement, the root is knocked off and another tree is constructed. The maximal number of trials is specified by maxConsecutiveFails. When the maxConsecutiveFails is reached, no new tree will be constructed and existing trees will be used for classification.

To use other tree classifier than J48, try

Classify -> Choose -> meta -> MDMT

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