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Table 1 Differences between Data Mining Algorithms

From: Data mining for classification of power quality problems using WEKA and the effect of attributes on classification accuracy

Properties

J48

Random Tree

Random Forest

Attributes available at each decision node

All

Random Subset

Random Subset

Selection of attributes at each decision node

Highest information gain among all

Best among a random subset

Best among a random subset

Number of trees

One

One

Many

Data samples used for training

All

All

Different data sets for different trees, randomly chosen

Final result of Classification

Based on the leaf node reached

Based on the leaf node reached

Based on majority voting from all the trees