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This project contains two files. A DecisionTree.py and a Driver.py file. I have used two datasets for my analysis. These are: Iris Dataset. Pima-Indian Dataset. Here I have introduced a pruning mechanism where I am pruning the generated tree on each internal node and then if the testing accuracy is more for the pruned dataset I am printing the p…

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DecisionTreePruning

This project contains two files. A DecisionTree.py and a Driver.py file. I have used two datasets for my analysis. These are:
Iris Dataset. Pima-Indian Dataset.

Here I have introduced a pruning mechanism where I am pruning the generated tree on each internal node and then if the testing accuracy is more for the pruned dataset I am printing the pruned tree along with its accuracy.

For 10 runs:
Accuracy before pruning : 70%

Best Accuracy obtained after pruning : 99%

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This project contains two files. A DecisionTree.py and a Driver.py file. I have used two datasets for my analysis. These are: Iris Dataset. Pima-Indian Dataset. Here I have introduced a pruning mechanism where I am pruning the generated tree on each internal node and then if the testing accuracy is more for the pruned dataset I am printing the p…

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