ComputeLogisticRegressionStandardDeviation Class

Definition

Namespace:

Microsoft.ML.Trainers

Assembly:

Microsoft.ML.StandardTrainers.dll

Package:

Microsoft.ML v3.0.1

Computes the standard deviation matrix of each of the non-zero training weights, needed to calculate further the standard deviation, p-value and z-Score. Use this class' implementation in the Microsoft.ML.Mkl.Components package which uses Intel Math Kernel Library. Due to the existence of regularization, an approximation is used to compute the variances of the trained linear coefficients.

public abstract class ComputeLogisticRegressionStandardDeviation

type ComputeLogisticRegressionStandardDeviation = class

Public MustInherit Class ComputeLogisticRegressionStandardDeviation

Inheritance

Object

ComputeLogisticRegressionStandardDeviation

Derived

Microsoft.ML.Trainers.ComputeLRTrainingStdThroughMkl

Constructors

ComputeLogisticRegressionStandardDeviation()

Methods

ComputeStandardDeviation(Double[], Int32[], Int32, Int32, IChannel, Single)

Computes the standard deviation matrix of each of the non-zero training weights, needed to calculate further the standard deviation, p-value and z-Score. The calculations are not part of Microsoft.ML package, due to the size of MKL. If you need these calculations, add the Microsoft.ML.Mkl.Components package, and initialize ComputeStandardDeviation to the ComputeLogisticRegressionStandardDeviation implementation in the Microsoft.ML.Mkl.Components package. Due to the existence of regularization, an approximation is used to compute the variances of the trained linear coefficients.