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ComputeLogisticRegressionStandardDeviation.ComputeStandardDeviation Metode

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Definisi

Ruang nama:
Microsoft.ML.Trainers
Rakitan:
Microsoft.ML.StandardTrainers.dll
Paket:
Microsoft.ML v3.0.1
Paket:
Microsoft.ML v1.0.0
Paket:
Microsoft.ML v1.1.0
Paket:
Microsoft.ML v1.2.0
Paket:
Microsoft.ML v1.3.1
Paket:
Microsoft.ML v1.4.0
Paket:
Microsoft.ML v1.5.5
Paket:
Microsoft.ML v1.6.0
Paket:
Microsoft.ML v1.7.0
Paket:
Microsoft.ML v2.0.0

Menghitung matriks deviasi standar dari masing-masing bobot pelatihan non-nol, yang diperlukan untuk menghitung lebih lanjut deviasi standar, nilai p, dan z-Score. Perhitungan bukan bagian dari paket Microsoft.ML, karena ukuran MKL. Jika Anda memerlukan perhitungan ini, tambahkan paket Microsoft.ML.Mkl.Components, dan inisialisasi ComputeStandardDeviation ke ComputeLogisticRegressionStandardDeviation implementasi dalam paket Microsoft.ML.Mkl.Components. Karena adanya regularisasi, perkiraan digunakan untuk menghitung varian koefisien linier terlatih.

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)

Parameter

hessian
Double[]
weightIndices
Int32[]
parametersCount
Int32
currentWeightsCount
Int32
ch
IChannel
l2Weight
Single

Mengembalikan

VBuffer<Single>

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