Function
Static Public Summary | ||
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dropoutLayer(layer: Matrix, pDropout: number): Matrix Randomly drop values from a layer. |
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Return a sample from a normal distribution. |
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Return a matrix, all of whose element are sampled from the standard normal distribution. |
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sigmoidPrime(z: Matrix): Matrix Derivative of the sigmoid function. |
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vectorizedResult(j: number): Matrix Return a 10-dimensional unit vector with a 1.0 in the j'th position and zeroes elsewhere. This is used to convert a digit (0...9) into a corresponding desired output from the neural network. |
Static Public
public dropoutLayer(layer: Matrix, pDropout: number): Matrix source
import {dropoutLayer} from 'js-mind/src/lib.js'
Randomly drop values from a layer.
Params:
Name | Type | Attribute | Description |
layer | Matrix | ||
pDropout | number | probability to drop out value for each element |
Return:
Matrix | converted matrix with the same nRow, nCol |
public norm(mu: number, sigma: number): number source
import {norm} from 'js-mind/src/lib.js'
Return a sample from a normal distribution.
public randn(rows: number, cols: number): Matrix source
import {randn} from 'js-mind/src/lib.js'
Return a matrix, all of whose element are sampled from the standard normal distribution. see http://d.hatena.ne.jp/iroiro123/20111210/1323515616
Return:
Matrix | random matrix |
public sigmoidPrime(z: Matrix): Matrix source
import {sigmoidPrime} from 'js-mind/src/lib.js'
Derivative of the sigmoid function.
Params:
Name | Type | Attribute | Description |
z | Matrix |
Return:
Matrix | converted matrix with the same nRow, nCol |
public vectorizedResult(j: number): Matrix source
import {vectorizedResult} from 'js-mind/src/lib.js'
Return a 10-dimensional unit vector with a 1.0 in the j'th position and zeroes elsewhere. This is used to convert a digit (0...9) into a corresponding desired output from the neural network.
Params:
Name | Type | Attribute | Description |
j | number | interger: zero to nine |
Return:
Matrix | 10x1 |