User:Sooshie/Books/Statistical Learning

Statistical Learning

 * Statistics
 * Exploratory data analysis
 * Probability_distribution
 * Variance
 * Analysis_of_Variance
 * Covariate
 * Statistical inference
 * Algorithmic inference
 * Bayesian inference
 * Base rate
 * Bias (statistics)
 * Gibbs sampling
 * Cross-entropy method
 * Latent variable
 * Maximum a posteriori estimation
 * Expectation–maximization algorithm
 * Expectation propagation
 * Kullback–Leibler divergence
 * Generative model


 * Significance
 * Likelihood_ratio_test
 * Maximum_likelihood
 * Statistical_significance
 * Chi-squared_test
 * G-test
 * Pearson%27s_chi-squared_test
 * Yates%27s_correction_for_continuity
 * McNemar%27s_test


 * Statistical classification
 * Statistical classification
 * Probability matching
 * Discriminative model
 * Linear discriminant analysis
 * Multiclass LDA
 * Multiple discriminant analysis
 * Optimal discriminant analysis
 * Fisher kernel
 * Discriminant function analysis
 * Multilinear subspace learning
 * Quadratic classifier
 * Variable kernel density estimation
 * Category utility


 * Evaluation of Classification Models
 * Data classification (business intelligence)
 * Training set
 * Test set
 * Synthetic data
 * Cross-validation (statistics)
 * Loss function
 * Hinge loss
 * Generalization error
 * Type I and type II errors
 * Sensitivity and specificity
 * Precision and recall
 * F1 score
 * Confusion matrix
 * Matthews correlation coefficient
 * Receiver operating characteristic
 * Lift (data mining)
 * Stability in learning


 * Bayesian Learning Methods
 * Naive Bayes classifier
 * Averaged one-dependence estimators
 * Bayesian network
 * Bayesian additive regression kernels
 * Variational message passing


 * Markov Models
 * Markov model
 * Maximum-entropy Markov model
 * Hidden Markov model
 * Baum–Welch algorithm
 * Forward–backward algorithm
 * Hierarchical hidden Markov model
 * Markov logic network
 * Markov chain Monte Carlo
 * Markov random field
 * Conditional random field
 * Predictive state representation


 * Regression analysis
 * Outline of regression analysis
 * Regression analysis
 * Dependent and independent variables
 * Linear model
 * Linear regression
 * Least squares
 * Linear least squares (mathematics)
 * Local regression
 * Additive model
 * Antecedent variable
 * Autocorrelation
 * Backfitting algorithm
 * Bayesian linear regression
 * Bayesian multivariate linear regression
 * Binomial regression
 * Canonical analysis
 * Censored regression model
 * Coefficient of determination
 * Comparison of general and generalized linear models
 * Compressed sensing
 * Conditional change model
 * Controlling for a variable
 * Cross-sectional regression
 * Curve fitting
 * Deming regression
 * Design matrix
 * Difference in differences
 * Dummy variable (statistics)
 * Errors and residuals in statistics
 * Errors-in-variables models
 * Explained sum of squares
 * Explained variation
 * First-hitting-time model
 * Fixed effects model
 * Fraction of variance unexplained
 * Frisch–Waugh–Lovell theorem
 * General linear model
 * Generalized additive model
 * Generalized additive model for location, scale and shape
 * Generalized estimating equation
 * Generalized least squares
 * Generalized linear array model
 * Generalized linear mixed model
 * Generalized linear model
 * Growth curve
 * Guess value
 * Hat matrix
 * Heckman correction
 * Heteroscedasticity-consistent standard errors
 * Hosmer–Lemeshow test
 * Instrumental variable
 * Interaction (statistics)
 * Isotonic regression
 * Iteratively reweighted least squares
 * Kitchen sink regression
 * Lack-of-fit sum of squares
 * Leverage (statistics)
 * Limited dependent variable
 * Linear probability model
 * Mallows's Cp
 * Mean and predicted response
 * Mixed model
 * Moderation (statistics)
 * Moving least squares
 * Multicollinearity
 * Multiple correlation
 * Multivariate probit
 * Multivariate adaptive regression splines
 * Newey–West estimator
 * Non-linear least squares
 * Nonlinear regression


 * Logistic Regression
 * Logit
 * Multinomial logit
 * Logistic regression