GitHub / ishita48 / Breast-Cancer-Diagnosis-ML-model

This breast cancer diagnosis project evaluates various machine learning models to effectively classify breast masses as benign or malignant. SVM and Logistic Regression excel in identifying positive cases, leveraging their robust performance metrics, while Neural Networks show promising results and offer opportunities for further enhancement!

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PURL: pkg:github/ishita48/Breast-Cancer-Diagnosis-ML-model

Topics: colab-notebook, data-science, data-visualization, exploratory-data-analysis, gradient-boosting-regressor, jupyter-notebook, k-nearest-neighbours, logistic-regression, matplotlib, model-evaluation-metrics, neural-network, neural-networks, numpy, pandas, python, random-forest, support-vector-machine, tensorflow-keras

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• Readme
• Dependencies