User:Sulekhadileep/Books/Machine Learning Algorithms
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Machine Learning Algorithms
- 1. Regression Algorithms
- Ordinary least squares
- Linear regression
- Logistic regression
- Stepwise regression
- Multivariate adaptive regression splines
- Local regression
- 2. Instance-based Algorithms
- K-nearest neighbors algorithm
- Learning vector quantization
- Self-organizing map
- Tikhonov regularization
- 3. Regularization Algorithms
- Lasso (statistics)
- Elastic net regularization
- 3. Regularization Algorithms
- Tikhonov regularization
- Lasso (statistics)
- Elastic net regularization
- Least-angle regression
- Hyperparameter optimization
- 4. Decision Tree Algorithms
- Decision tree learning
- ID3 algorithm
- C4.5 algorithm
- Chi-square automatic interaction detection
- Decision stump
- 5. Bayesian Algorithms
- Naive Bayes classifier
- Averaged one-dependence estimators
- Bayesian network
- 6. Clustering Algorithms
- K-means clustering
- K-medians clustering
- Expectation–maximization algorithm
- Hierarchical clustering
- 7. Association Rule Learning Algorithms
- Association rule learning
- Apriori algorithm
- 8. Artificial Neural Network Algorithms
- Perceptron
- Backpropagation
- Hopfield network
- Radial basis function network
- 9. Deep Learning Algorithms
- Deep learning
- Deep belief network
- Convolutional neural network
- 10. Dimensionality Reduction Algorithms
- Principal component analysis
- Principal component regression
- Partial least squares regression
- Sammon mapping
- Multidimensional scaling
- Projection pursuit
- Linear discriminant analysis
- Quadratic classifier
- 11. Ensemble Algorithms
- Boosting (machine learning)
- Bootstrap aggregating
- AdaBoost
- Ensemble learning
- Gradient boosting
- Random forest
- 12. Other Algorithms
- Computational intelligence
- Computer vision
- Natural language processing
- Recommender system
- Reinforcement learning
- Graphical model
- I. Complete Reference
- Outline of machine learning
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