ComputeLogisticRegressionStandardDeviation.ComputeStandardDeviation 方法

定义

命名空间:

Microsoft.ML.Trainers

程序集:

Microsoft.ML.StandardTrainers.dll

包:

Microsoft.ML v3.0.1

计算进一步计算标准偏差、p 值和 z 分数所需的每个非零训练权重的标准偏差矩阵。 由于 MKL 的大小，计算不是 Microsoft.ML 包的一部分。 如果需要这些计算，请添加 Microsoft.ML.Mkl.Components 包，并初始化 ComputeStandardDeviation 到 ComputeLogisticRegressionStandardDeviation Microsoft.ML.Mkl.Components 包中的实现。 由于存在正则化，因此使用近似值来计算定型线性系数的方差。

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)

参数

hessian

Double[]

weightIndices

Int32[]

parametersCount

Int32

currentWeightsCount

Int32

ch

IChannel

l2Weight

Single

返回

VBuffer<Single>