ComputeLogisticRegressionStandardDeviation.ComputeStandardDeviation 方法

定義

命名空間:

Microsoft.ML.Trainers

組件:

Microsoft.ML.StandardTrainers.dll

套件:

Microsoft.ML v3.0.1

計算每個非零定型權數的標準差矩陣，以進一步計算標準差、p 值和 z-Score。 計算不是 Microsoft.ML 套件的一部分，因為 MKL 的大小。 如果您需要這些計算，請新增 Microsoft.ML.Mkl.Components 套件，並將 初始化 ComputeStandardDeviation 至 ComputeLogisticRegressionStandardDeviation Microsoft.ML.Mkl.Components 套件中的實作。 由於正規化存在，因此會使用近似值來計算定型線性係數的變異數。

public abstract Microsoft.ML.Data.VBuffer<float> ComputeStandardDeviation (double[] hessian, int[] weightIndices, int parametersCount, int currentWeightsCount, Microsoft.ML.Runtime.IChannel ch, float l2Weight);

abstract member ComputeStandardDeviation : double[] * int[] * int * int * Microsoft.ML.Runtime.IChannel * single -> Microsoft.ML.Data.VBuffer<single>

Public MustOverride Function ComputeStandardDeviation (hessian As Double(), weightIndices As Integer(), parametersCount As Integer, currentWeightsCount As Integer, ch As IChannel, l2Weight As Single) As VBuffer(Of Single)

參數

hessian

Double[]

weightIndices

Int32[]

parametersCount

Int32

currentWeightsCount

Int32

ch

IChannel

l2Weight

Single

傳回

VBuffer<Single>