- The objective of the project was to build various models and compare their prediction performance based on accuracy.
- Built models trained on logistic regression, SVM, KNN, and random forest.
- By comparing the prediction accuracy of these models, it was found that model trained on logistic regression performed the best in classifying the dataset.
- Tools used: Jupyter notebook
- Language: Python 3
- The dataset was imported from the scikit-learn package.
-
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The objective of the project was to build various models and compare their prediction performance based on accuracy.
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