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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