/**
@mainpage
MADlib is an open-source library for scalable in-database analytics. It provides data-parallel implementations of mathematical, statistical and machine learning methods for structured and unstructured data.
The MADlib mission: to foster widespread development of scalable analytic skills, by harnessing efforts from commercial practice, academic research, and open-source development.
Useful links:
- MADlib project site http://madlib.net/
- MADlib bug reporting site: http://jira.madlib.net/ and quick guide: https://github.com/madlib/madlib/wiki/Bug-reporting
Please refer to the Read-Me file for information
about incorporated third-party material. License information regarding MADlib
and included third-party libraries can be found inside the
license directory.
@defgroup grp_glm Generalized Linear Models
@defgroup grp_linreg Linear Regression
@ingroup grp_glm
@defgroup grp_logreg Logistic Regression
@ingroup grp_glm
@defgroup grp_mlogreg Multinomial Logistic Regression
@ingroup grp_glm
@defgroup grp_elasticnet Elastic Net Regularization
@ingroup grp_glm
@defgroup grp_cox_prop_hazards Cox-Proportional Hazards Regression
@ingroup grp_glm
@defgroup grp_robust Huber White Variance
@ingroup grp_glm
@defgroup grp_clustered_errors Clustered Variance
@ingroup grp_glm
@defgroup grp_marginal Marginal Effects
@ingroup grp_glm
@defgroup grp_validation Cross Validation
@defgroup grp_linear_solver Linear Systems
@defgroup grp_dense_linear_solver Dense Linear Systems
@ingroup grp_linear_solver
@defgroup grp_sparse_linear_solver Sparse Linear Systems
@ingroup grp_linear_solver
@defgroup grp_matrix_factorization Matrix Factorization
@defgroup grp_lmf Low-rank Matrix Factorization
@ingroup grp_matrix_factorization
@defgroup grp_svd Singular Value Decomposition
@ingroup grp_matrix_factorization
@defgroup grp_association_rules Association Rules
@defgroup grp_assoc_rules Apriori Algorithm
@ingroup grp_association_rules
@defgroup grp_clustering Clustering
@defgroup grp_kmeans k-Means Clustering
@ingroup grp_clustering
@defgroup grp_topic_modelling Topic Modelling
@defgroup grp_lda Latent Dirichlet Allocation
@ingroup grp_topic_modelling
@defgroup grp_desc_stats Descriptive Statistics
@defgroup grp_summary Summary
@ingroup grp_desc_stats
@defgroup grp_correlation Pearson's Correlation
@ingroup grp_desc_stats
@defgroup grp_stats Inferential Statistics
@defgroup grp_stats_tests Hypothesis Tests
@ingroup grp_stats
@defgroup grp_support Support Modules
@defgroup grp_array Array Operations
@ingroup grp_support
@defgroup grp_svec Sparse Vectors
@ingroup grp_support
@defgroup grp_prob Probability Functions
@ingroup grp_support
@defgroup grp_compatibility Compatibility
@ingroup grp_support
@defgroup grp_pca Principal Component Analysis
@defgroup grp_pca_train PCA Training
@ingroup grp_pca
@defgroup grp_pca_project PCA Projection
@ingroup grp_pca
@defgroup grp_tsa Time Series Analysis
@defgroup grp_arima ARIMA
@ingroup grp_tsa
@defgroup grp_early_stage Early Stage Development
@defgroup grp_bayes Naive Bayes Classification
@ingroup grp_early_stage
@defgroup grp_dectree Decision Tree
@ingroup grp_early_stage
@defgroup grp_rf Random Forest
@ingroup grp_early_stage
@defgroup grp_kernmach Support Vector Machines
@ingroup grp_early_stage
@defgroup grp_crf Conditional Random Field
@ingroup grp_early_stage
@defgroup grp_sketches Sketch-based Estimators
@ingroup grp_early_stage
@defgroup grp_countmin CountMin (Cormode-Muthukrishnan)
@ingroup grp_sketches
@defgroup grp_fmsketch FM (Flajolet-Martin)
@ingroup grp_sketches
@defgroup grp_mfvsketch MFV (Most Frequent Values)
@ingroup grp_sketches
@defgroup grp_profile Profile
@ingroup grp_early_stage
@defgroup grp_quantile Quantile
@ingroup grp_early_stage
@defgroup grp_cg Conjugate Gradient
@ingroup grp_early_stage
@defgroup grp_sample Random Sampling
@ingroup grp_early_stage
@defgroup grp_linalg Linear Algebra Operations
@ingroup grp_early_stage
@defgroup grp_utilities DB Administrator Utilities
@ingroup grp_early_stage
*/