Machine learning algorithm classification
Supervised learning
Unsupervised learning
Semi-supervised learning
Reinforcement learning
Supervised Regression
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Simple and multiple linear regression
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Decision tree or forest regression
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Artificial Neural networks
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Ordinal regression
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Poisson regression
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Nearest neighbor methods (e.g., k-NN or k-Nearest Neighbors)
Supervised Two-class & Multi-class Classification
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Logistic regression and multinomial regression
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Artificial Neural networks
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Decision tree, forest, and jungles
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SVM (support vector machine)
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Perceptron methods
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Bayesian classifiers (e.g., Naive Bayes)
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Nearest neighbor methods (e.g., k-NN or k-Nearest Neighbors)
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One versus all multiclass
Unsupervised
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K-means clustering
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Hierarchical clustering
Anomaly Detection
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Support vector machine (one class)
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PCA (Principle component analysis)
ref
- Machine Learning Algorithm Overview [medium]