2.1.0
User Documentation for Apache MADlib
Early Stage Development

Detailed Description

Implementations which are in an early stage of development. Interface and implementation are subject to change.

Modules

 Conjugate Gradient
 Finds the solution to the function \( \boldsymbol Ax = \boldsymbol b \), where \(A\) is a symmetric, positive-definite matrix and \(x\) and \( \boldsymbol b \) are vectors.
 
 DBSCAN
 Partitions a set of observations into clusters of arbitrary shape based on the density of nearby neighbors.
 
 Naive Bayes Classification
 Constructs a classification model from a dataset where each attribute independently contributes to the probability that a data point belongs to a category.
 
 Random Sampling
 Provides utility functions for sampling operations.
 
 XGBoost
 This module allows you to use SQL to build gradient boosted tree models designed in XGBoost [1].