Evaluate on three different ML model for feature selection using Breast cancer data.

Last update: Mar 17, 2022

Overview

Anomaly-detection-Feature-Selection

Evaluate on three different ML model for feature selection using Breast cancer data.

ML models: SVM, KNN and MLP.

Report recall and Precision of each model.

Data

Features are computed from a digitized image of a fine needle aspirate (FNA) of a breast mass. They describe characteristics of the cell nuclei present in the image. n the 3-dimensional space is that described in: [K. P. Bennett and O. L. Mangasarian: "Robust Linear Programming Discrimination of Two Linearly Inseparable Sets", Optimization Methods and Software 1, 1992, 23-34]

More details about data : https://www.kaggle.com/uciml/breast-cancer-wisconsin-data

Owner

Tarek idrees

Bioinformatics Engineer👨‍🔬

GitHub Repository

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Evaluate on three different ML model for feature selection using Breast cancer data.

Related tags

Overview

Anomaly-detection-Feature-Selection

Data

Owner

Tarek idrees

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