Logistic Regression, Machine Learning, Classification, Regularization, Algorithms.
well. The disadvantages are as follows: It can have low performance on datasets of small size. If the data is not/can’t be made linearly separable, logistic regression may not be the most suitable model to apply to the dataset. If the features in the dataset are multicollinear, then the model may