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Real world data was modeled to predict if the patient had benign or malignant breast cancer using K-Nearest-Neighbors and SVM Classifiers.

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Tejas1415/Breast_Cancer-Classification-through-KNN_Classifier.

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Breast_Cancer-Classification-through-KNN_Classifier.

A simple yet important project to start off with ML projects.

The dataset has been uploaded to the Git but it is recommended to go to: archive.ics.uci.edu/ml/datasets.html and look at "Breast_cancer_wisconsin.data dataset. To understand what the data represents they have a clear documentation which needs to be looked at.

KNN classifier was proved to be efficient during the classification over the input data with over 97% accuracy. SVM classifier could not achieve efficient results as compared to the KNN classifier.

The code is well commented and self explanatory, incase of further doubts feel free to contact me at tejastk.reddy@gmail.com

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Real world data was modeled to predict if the patient had benign or malignant breast cancer using K-Nearest-Neighbors and SVM Classifiers.

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