User:Sulekhadileep/Books/MachineLearningAlgorithms

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


 * 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