-
Random Forest: Combines multiple decision trees for accurate, robust classification and regression.
-
SVM: Identifies optimal hyperplane to maximize class separation with high accuracy.
-
K-Nearest Neighbors: Classifies data points by majority vote of nearest neighbors.
-
Decision Tree: Divides data into branches using feature splits for clear decisions.
-
Logistic Regression: Uses a logistic function to model the probability of a binary outcome.
-
Naive Bayes: Applies Bayes' Theorem with strong (naive) independence assumptions to classify data.
rafaelfgx/AI
Folders and files
| Name | Name | Last commit date | ||
|---|---|---|---|---|