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Feature selection comparison in breath cancer dataset

Python 100.00%

artificial-intelligence cancer-data chi comparison feature-engineering feature-extraction feature-selection kaggel-dataset lasso machine-learning modeling pca preprocessing random-forest univariate data-science python statistics

feature-selcetion's Introduction

Feature-selcetion comparision

Feature selection comparison in breath cancer dataset analysis and preprocessing in feature selection and engeniering and modeling with Random Forest. The model has been test with 6 different feature selection method as comparision of accuracy in machine learning model.

The feature selection methods :

Univaraint
PCA
Changing Lasso
recursive_feature_elimination
sequentialfeatureselector_method
model_based_method

As Random Forest has its own way to feature selection by cost function of Entrupy or Gini. For analysis the performances of the feature selections methods Random Forest is compatible benchmark as scoring and comparision of feature selection methods.

This machin learning has been tested for Supervised Binary classification of breath canser data set.

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