Chi-Squared For Feature Selection using SelectKBest
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Updated
May 28, 2021 - Jupyter Notebook
Chi-Squared For Feature Selection using SelectKBest
With the Student Alcohol Consumption data set, we predict high or low alcohol consumption of students.
Feature Selection is the process where you automatically or manually select those features which contribute most to your prediction variable or output in which you are interested in. Having irrelevant features in your data can decrease the accuracy of the models and make your model learn based on irrelevant features.
Heart Attack Prediction by implementing Feature Selection such as SelectKBest & Recursive Feature Elimination
Implementing SelectKBest from Scratch for a Regression problem
Before training a model or feed a model, first priority is on data,not in model. The more data is preprocessed and engineered the more model will learn. Feature selectio one of the methods processing data before feeding the model. Various feature selection techniques is shown here.
This repository contains introductory notebooks for Decision tree
Predictive modeling project by implementing KNN regression model.
Data and code for a machine learning exercise in which I predict the development of depression.
pipelines chains together multiple steps so that the output of each step is used as input to the next step
A financial institution wants to accurately predict the probability of loanee/borrower defaulting on a vehicle loan in the first EMI on the due date.
The Dairy Goods Sales Dataset provides a detailed and comprehensive collection of data related to dairy farms, dairy products, sales, and inventory management.
Logistic Regression project for Banking Marketing Campaign.
Machine Learning Techniques in Lung Cancer Prediction
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