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Compare ML Classifiers: Logistic, Tree, KNN by anuj rawat is a document available to read on EtoBox.

What is Compare ML Classifiers: Logistic, Tree, KNN about?

The document outlines a task to implement Logistic Regression, Decision Tree, and KNN classifiers using a dataset from customers.csv, with an emphasis on estimating their accuracy. It includes steps for loading, preprocessing the data, and training the models, as well as evaluating their performance. The accuracy results indicate Logistic Regression performed the best at approximately 81.82% accuracy, followed by KNN at 71.59% and Decision Tree at 61.36%.

Author

anuj rawat

Language

EN