Published September 29, 2022
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Grid Search Hyper-Parameter Tuning and K-Means Clustering toImprove the Decision Tree Accuracy
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Representation and quality of the instance data are the foremost factors that affects classification accuracy of the statistical - based method Decision tree algorithm which gives less accuracy for binary classification problems. Experiments shows that by using clustering and hyper-parameter tuning, the decision tree accuracy can be achieved above 95%, better than the 75% recognition using decision tree alone.
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IJISRT22SEP233.pdf
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