Logistic Regression: 83.42%
Decision Tree: 78.85%
Random Forest: 82%
Support Vector Machine: 83.41%
Note:
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The dataset consists of 14columns: 6 numerical + 8 categorical columns.
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Data preprocessing has been done and also PCA has been applied on numerical columns before applying the classification algorithms