如何可视化隐藏神经元学习的表示？ [英] How to visualize the representations learnt by hidden neurons ?

问题描述

我已经训练了一个神经网络来识别手写数字。它有784个输入，1个隐藏层有50个神经元，输出层有10个神经元。现在我想要想象隐藏神经元学到的表示。如何做到这一点？ ？

I have trained a neural network to identify handwritten digits.It has 784 inputs,1 hidden layer with 50 neurons and output layer with 10 neurons.Now I want to visualize the representations learnt by hidden neurons.How can that be done ??

推荐答案

人工神经网络学到的知识就是它的重量，而不是隐藏的神经元。隐藏神经元是计算节点，它从输入层获取输入及其相关权重，将它们通过一些激活函数来产生输出层的输出。看看这个：

AI：神经网络初学者（第1部分，共3部分） [ ^ ]。

如果您正在寻找能够生成其学习成果图形表示的机器学习算法，请尝试使用SOM。看看这个：自组织地图揭秘 [ ^ ]

The knowledge learnt by an ANN is its snaptic weights, not the hidden neurons. Hidden neurons are computation nodes that take the inputs and their associated weights from the input layer, put them through some activation function to produce the outputs for the output layer. Check this out:
AI : Neural Network for beginners (Part 1 of 3)[^].
If you are looking for some machine learning algorithm that can produce graphical representation of its learning outcome, try SOM. Check this out: Self-organizing Map Demystified[^]

这篇关于如何可视化隐藏神经元学习的表示？的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！