GitHub - agciss/Machine-Learning-Classification-for-Breast-Cancer-Data-Set: Training the logistic regression, linear svm, kernel svm, naïve bayes, decision tree, and random forest classification models. Making the confusion matrix and accuracy score for all classification models

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Name		Name	Last commit message	Last commit date
Latest commit History 1 Commit
Template Decision Tree - Data Breast Cancer.ipynb		Template Decision Tree - Data Breast Cancer.ipynb
Template K-Nearest Neighbors (K-NN) - Data Breast Cancer.ipynb		Template K-Nearest Neighbors (K-NN) - Data Breast Cancer.ipynb
Template Kernel SVM (RBF) - Data Breast Cancer.ipynb		Template Kernel SVM (RBF) - Data Breast Cancer.ipynb
Template Linear Support Vector Machine (SVM) - Data Breast Cancer.ipynb		Template Linear Support Vector Machine (SVM) - Data Breast Cancer.ipynb
Template Logistic Regression - Data Breast Cancer.ipynb		Template Logistic Regression - Data Breast Cancer.ipynb
Template Naive Bayes - Data Breast Cancer.ipynb		Template Naive Bayes - Data Breast Cancer.ipynb
Template Random Forest - Data Breast Cancer.ipynb		Template Random Forest - Data Breast Cancer.ipynb

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Training the logistic regression, linear svm, kernel svm, naïve bayes, decision tree, and random forest classification models. Making the confusion matrix and accuracy score for all classification models