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Predictions on the breast cancer data set after feature reduction

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csaiprashant/breast-cancer-wisconsin

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Predictions on the breast cancer Wisconsin data set after feature reduction

In this repository, I demonstrate the standard workflow of a data science project which include steps like

  • data preprocessing ,
  • exploratory data analysis.
  • building the machine learning model, and
  • improving model accuracy using feature reduction

I used the Breast Cancer Wisconsin (Diagnostic) Data Set and trained models like Linear Discriminant Analysis, Random Forest Classifier and Gradient Boosting Decision Trees. To reduce the features, I used Principal Component Analysis and Feature Importance.