ComputeLogisticRegressionStandardDeviation Class
Definition
Important
Some information relates to prerelease product that may be substantially modified before it’s released. Microsoft makes no warranties, express or implied, with respect to the information provided here.
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 ComputeLogisticRegressionStandardDeviationtype ComputeLogisticRegressionStandardDeviation = classPublic MustInherit Class ComputeLogisticRegressionStandardDeviation- Inheritance
-
ComputeLogisticRegressionStandardDeviation
- Derived
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. |