# MklComponentsCatalog Class

## Definition

Collection of extension methods for RegressionCatalog.RegressionTrainers, BinaryClassificationCatalog.BinaryClassificationTrainers, and TransformsCatalog to create MKL (Math Kernel Library) trainer and transform components.

public static class MklComponentsCatalog
type MklComponentsCatalog = class
Public Module MklComponentsCatalog
Inheritance
MklComponentsCatalog

## Methods

 Create OlsTrainer with advanced options, which predicts a target using a linear regression model. Create OlsTrainer, which predicts a target using a linear regression model. Create SymbolicSgdLogisticRegressionBinaryTrainer, which predicts a target using a linear binary classification model trained over boolean label data. Stochastic gradient descent (SGD) is an iterative algorithm that optimizes a differentiable objective function. The SymbolicSgdLogisticRegressionBinaryTrainer parallelizes SGD using symbolic execution. Create SymbolicSgdLogisticRegressionBinaryTrainer with advanced options, which predicts a target using a linear binary classification model trained over boolean label data. Stochastic gradient descent (SGD) is an iterative algorithm that optimizes a differentiable objective function. The SymbolicSgdLogisticRegressionBinaryTrainer parallelizes SGD using symbolic execution. Takes column filled with a vector of random variables with a known covariance matrix into a set of new variables whose covariance is the identity matrix, meaning that they are uncorrelated and each have variance 1.