Decision Tree in Python : Metaprotein

Python code

R code

Data Analysis Results

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Decision Tree

We have implemented the following criteria to split nodes in our Decision Trees for comparison of accuracy

• Gini Index
• Information Gain (Entropy)

We have taken (2/3)rd of our Metaprotein Dataset to be used as Training Dataset & (1/3)rd to be used as Testing Dataset

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Gini Index

Confusion Matrix: Prediction on Test Dataset

Accuracy = 72/97 = 79.16 %

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Information Gain (Entropy)

Confusion Matrix: Prediction on Test Dataset

Accuracy = 72/97 = 70.83 %

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