Internship← Artificial Intelligence & Machine Learning learning pathArtificial Intelligence & Machine Learning · Module 5 of 10
Classification models
Predict categories with classifiers.
📖 Key ideas
- Logistic regression predicts probabilities for classes.
- k-Nearest Neighbours votes using nearby examples.
- Decision trees split data by questions.
- Random forests and gradient boosting (XGBoost) combine many trees.
- SVMs find the best separating boundary.
💡 Real-life example: A decision tree is a game of 20 questions leading to a final answer.
Logistic regressionProbability-based classifier
k-NNClassifies by nearest neighbours
Random forestEnsemble of decision trees
XGBoostGradient boosting library