Logistic Regression
Logistic regression is a statistical model used for binary classification problems. It estimates the probability of an instance belonging to a particular class using a logistic function. Logistic regression is simple yet effective and can be extended to handle multiclass classification tasks using techniques such as one-vs-rest or softmax regression.
| Precision: | 75.78% |
| Accuracy: | 88.0% |
| Recall: | 87.39% |
| F1 Score: | 81.17% |
| ROC AUC Score: | 87.82% |