https://github.com/ethanhe42/neural-network-regression

fit a sine function with 2 layers neural network
https://github.com/ethanhe42/neural-network-regression

Last synced: about 1 month ago
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fit a sine function with 2 layers neural network

• Host: GitHub
• URL: https://github.com/ethanhe42/neural-network-regression
• Owner: ethanhe42
• Created: 2016-11-11T14:29:35.000Z (about 8 years ago)
• Default Branch: master
• Last Pushed: 2016-12-04T13:43:35.000Z (almost 8 years ago)
• Last Synced: 2024-04-14T17:45:01.240Z (7 months ago)
• Language: Python
• Size: 8.17 MB
• Stars: 2
• Watchers: 2
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
### Single Layer neural network

Single Layer neural network's performence is not so good.  

Which have accuracy of 55% on CIFAR-10  

However, with two images preprocessing techniques(PCA whintening and Kmeans), it can reach 75% on CIFAR-10  

[Detailed report in here](https://github.com/yihui-he/Single-Layer-neural-network-with-PCAwhitening-Kmeans/blob/master/report/mp1_Yihui%20He.pdf)  

reference:  

["Analysis Single Layer Unsupervised Feature Learning"](https://github.com/yihui-he/Single-Layer-neural-network-with-PCAwhitening-Kmeans/blob/master/paper/AnalysisSingleLayerUnsupervisedFeatureLearning.pdf)  

#### How to run  

1. Put cifar-10 dataset in ./dataset

2. run python redo.py dataset

#### files description

neural_net.py implement the neural net  

redo.py implement preprocessing  

The accuracy of different combinations of hyperparameters without preprocessing are shown in two *.csv* files 

[here](https://github.com/yihui-he/Single-Layer-neural-network-with-PCAwhitening-Kmeans/blob/master/fine_grained_nn.csv) and [here](https://github.com/yihui-he/Single-Layer-neural-network-with-PCAwhitening-Kmeans/blob/master/naive_nn.csv)  

Other files are not important, written for comparing different techniques and searching for parameters  

  

  

######If you have any questions, I'm glad to discuss with you.

# neural-network-regression