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]. | |