Machine Learning Algorithms
Supervised
Unsupervised
- Task Driven
- Data Driven
(predict next value)
(idenfity clusters)
Continuous Target
Categorical Target
Reinforcement
- Learn from mistakes
No Target Variable
Semi - supervised
Active Learning
Clustering:
Regression:
- Linear Regression
- Logistic Regression
- Multiple linear regression
- Polynomial Regression
- Naive Bayes
- BIRCH
Classification
•- DBSCAN
- KNN
•- Expectation-maximization (EM)
- DBScan
•- Fuzzy clustering
-SVM
•- Hierarchical Clustering
- Hierarchical Cluster Analysis
•- K-means clustering
•- K-medians
•- Mean-shift
•- OPTICS algorithm
Decision Tree
Anomaly Detection:
- k-nearest neighbors classification (k-NN)
•- Local outlier facto
•- Isolation Forest
Random Forest
Association Learning
- Apriori
- Eciat
Dimentionality Reduction
Recommender systems:
Deep Learning