Difference between logistic regression and svm

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Accepted Answer

Logistic regression is a linear model used for binary classification, while SVM is a non-linear model that can handle complex decision boundaries.

Logistic regression is a probabilistic model that predicts the probability of a binary outcome based on input features.
SVM aims to find the hyperplane that best separates the classes in a high-dimensional space.
Logistic regression is more interpretable and easier to implement, while SVM can handle non-linear decision boundaries through kernel tricks.
Logistic regression is sensitive to outliers, while SVM is less affected by them.
Example: Logistic regression can be used to predict whether a customer will buy a product (yes/no), while SVM can be used for image classification tasks.

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