default value check [fitnet]

2022 12 19
1 个回答
更新时间：2023 2 22
7 次查看（30 天）

0 个投票

using fitnet, i made a prediction model. so i have to explain how to make it and how to train, so i would like to know the defaults values of the function 'fitnet', for example, i would like to know the initial weight vector or what sigmoid function it uses. how can i know them?? thank you in advance.

请先登录，再回答此问题。

回答（1 个）

Rohit
Rohit 2023-2-22
Ran in:

0 个投票

Ran in:
When we use fitnet, it returns a neural network object. We can inspect this object for the weight values before and after training, and all other things related to the model.
net=fitnet(10) % in output we can see weight and bias parameters
net = Neural Network name: 'Function Fitting Neural Network' userdata: (your custom info) dimensions: numInputs: 1 numLayers: 2 numOutputs: 1 numInputDelays: 0 numLayerDelays: 0 numFeedbackDelays: 0 numWeightElements: 10 sampleTime: 1 connections: biasConnect: [1; 1] inputConnect: [1; 0] layerConnect: [0 0; 1 0] outputConnect: [0 1] subobjects: input: Equivalent to inputs{1} output: Equivalent to outputs{2} inputs: {1x1 cell array of 1 input} layers: {2x1 cell array of 2 layers} outputs: {1x2 cell array of 1 output} biases: {2x1 cell array of 2 biases} inputWeights: {2x1 cell array of 1 weight} layerWeights: {2x2 cell array of 1 weight} functions: adaptFcn: 'adaptwb' adaptParam: (none) derivFcn: 'defaultderiv' divideFcn: 'dividerand' divideParam: .trainRatio, .valRatio, .testRatio divideMode: 'sample' initFcn: 'initlay' performFcn: 'mse' performParam: .regularization, .normalization plotFcns: {'plotperform', 'plottrainstate', 'ploterrhist', 'plotregression', 'plotfit'} plotParams: {1x5 cell array of 5 params} trainFcn: 'trainlm' trainParam: .showWindow, .showCommandLine, .show, .epochs, .time, .goal, .min_grad, .max_fail, .mu, .mu_dec, .mu_inc, .mu_max weight and bias values: IW: {2x1 cell} containing 1 input weight matrix LW: {2x2 cell} containing 1 layer weight matrix b: {2x1 cell} containing 2 bias vectors methods: adapt: Learn while in continuous use configure: Configure inputs & outputs gensim: Generate Simulink model init: Initialize weights & biases perform: Calculate performance sim: Evaluate network outputs given inputs train: Train network with examples view: View diagram unconfigure: Unconfigure inputs & outputs
net.b{1} %getting initial bias value
ans = 10×1
0 0 0 0 0 0 0 0 0 0

类别

在 帮助中心 和 File Exchange 中查找有关 Semantic Segmentation 的更多信息

标签

提问:

인국 강
인국 강
2022-12-19

回答：

Rohit
Rohit
2023-2-22

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by