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I have tested the decision tree with and without randomness.
So, my results are as follows: Note: The average accuracy for the ID3 Algorithm with discrete splitting (random shuffling) can change a little as the code is using random shuffling.
boundaries for more than 2 classes) which is then used to classify new points.So, my results are as follows: Part d) Accuracy results for your improvements?For this section, I have used discrete splitting of the data along with other improvements as mentioned above.(If you want to learn more about the bias-variance tradeoff, check out Scott Roe’s Blog post.You can mess around with the value of K and watch the decision boundary change!