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Statistics - Adjusted R^2
Statistics - Akaike information criterion (AIC)
Data Mining - Algorithms
Statistics - Binary logistic regression
Data Mining - Decision boundary Visualization
Statistics - (Case-control|retrospective) sampling
Statistics - (Confidence|likelihood) (Prediction probabilities|Probability classification)
Statistics Learning - Discriminant analysis
Data Mining - (Discriminative|conditional) models
Data Mining - Elastic Net Model
Statistics - Generalized Linear Models (GLM) - Extensions of the Linear Model
Loss functions (Incorrect predictions penalty)
Statistics Learning - Multi-variant logistic regression
Statistics - (Multiclass Logistic|multinomial) Regression
Data Mining - (Global) Polynomial Regression (Degree)
Data Mining - Probit Regression (probability on binary problem)
Data Mining - Random forest
Statistics - Regression
(Machine learning|Inverse problems) - Regularization
Machine Learning - (Univariate|Simple) Logistic regression
Statistics vs (Machine Learning|Data Mining)
R - K-fold cross-validation (with Leave-one-out)
R - Logistic Regression
data_mining/logistic_regression.txt
· Last modified: 2015/07/13 21:42 by
gerardnico