Supervised Learning

Detailed Description

Methods to perform a variety of supervised learning tasks.

Modules
	Conditional Random Field
	Constructs a Conditional Random Fields (CRF) model for labeling sequential data.
	k-Nearest Neighbors
	Finds \(k\) nearest data points to the given data point and outputs majority vote value of output classes for classification, or average value of target values for regression.
	Neural Network
	Solves classification and regression problems with several fully connected layers and non-linear activation functions.
	Regression Models
	A collection of methods for modeling conditional expectation of a response variable.
	Support Vector Machines
	Solves classification and regression problems by separating data with a hyperplane or other nonlinear decision boundary.
	Tree Methods
	A collection of recursive partitioning (tree) methods.