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Feature Selection with SelectKBest by RAHUL DARANDALE is a document available to read on EtoBox.
What is Feature Selection with SelectKBest about?
This document describes a practical machine learning exercise to extract and select features from a mobile phone sales dataset to predict price. The dataset contains 21 variables describing phone specifications and the goal is to determine which factors most affect price. The program loads the dataset, selects the top 13 important features using a chi-squared test, and displays that pixel width, RAM, and pixel height have the highest scores, indicating they are best for predicting price.
- Author
- RAHUL DARANDALE
- Language
- EN