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Machine Learning Algorithms
A diverse array of machine learning algorithms exists, each categorized by distinct methodologies and applications. Dimensionality reduction techniques such as PCA and LDA are crucial for simplifying complex datasets.
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Machine Learning Algorithms Grouped By Similarity Others Feature selection Performance measures Algorithm accuracy evaluation SVR SVM Ensemble GBRT Blending AdaBoost Bagging Boosting GBM Random Forest Dimensionality Reduction LDA RDA QDA MDA Partial Least Squares Discriminant Analysis Projection Pursuit MDS Sammon Mapping PLSR PCR PCA Deep Learning Stacked Auto-Encoders CNN DBN DBM Artificial Neural Networks RBFN Hopfield Network Back-Propagation Perceptron Rule System RIPPER ZeroR OneR Cubist Association rule learning Eclat Apriori Clustering Hierarchical Clustering Expectation Maximization k-Medians k-Means Bayesian BN Multinomial Naive Bayes Gaussian Naive Bayes BBN AODE Navie Bayes Decision Tree M5 Conditional Decision Trees Decision Stump CHAID C4.5 & C5.0 ID3 CART Regularization LARS Elastic Net LASSO Ridge Regression Instance Based LWL SOM LVQ kNN Regression Logistic Regression LOESS MARS Stepwise Regression OLSR Learner Regression
