- Supervised Learning
a) Classification
Nearest Neighbors
Naive Bayes
Perceptron
Linear Support Vector Machines
Logistic Regression
Maximum Entropy
Decision Trees
Random Forest
Feed-forward Neural Network
AdaBoost
b) Regression
Nearest Neighbors
Linear Regression
Decision Trees
Random Forest
Feed-forward Neural Network
Gradient Boosting
c) Ranking
RankNet
- Unsupervised Learning
a) Clustering:
K-Means
b) Decomposition:
PCA