https://github.com/mohabmes/stocknn

Stock Market Prediction Using Neural Network Models (Backpropagation, RNN, RBF) Keras with Tensorflow backend
https://github.com/mohabmes/stocknn

keras neural-network stock-price-prediction

Last synced: 3 months ago
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Stock Market Prediction Using Neural Network Models (Backpropagation, RNN, RBF) Keras with Tensorflow backend

• Host: GitHub
• URL: https://github.com/mohabmes/stocknn
• Owner: mohabmes
• Created: 2018-03-24T23:53:43.000Z (almost 7 years ago)
• Default Branch: master
• Last Pushed: 2018-08-31T18:21:08.000Z (over 6 years ago)
• Last Synced: 2024-10-11T09:22:01.664Z (3 months ago)
• Topics: keras, neural-network, stock-price-prediction
• Language: Python
• Homepage:
• Size: 166 KB
• Stars: 47
• Watchers: 4
• Forks: 25
• Open Issues: 4
• Metadata Files:
  • Readme: README.md

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README

        
# StockNN

Stock Prices Prediction Using Neural Network Models (Backpropagation, RNN LSTM, RBF) implemented in keras with Tensorflow backend to predict the daily closing price.

## Class Version Usage

```

snn = stocknn().RNN()

snn = snn.preprocess('AAPL.csv', test_size=0.2)

snn = snn.train(batch_size=32, epochs=50)

```

or

```

snn = stocknn().BKP().preprocess('AAPL.csv', test_size=0.5).train(batch_size=16, epochs=25)

```

```

model = snn.save_model('AAPL')

mape = snn.test(model)[0]

pred = snn.predict(100)[1]

```

#### StockNN Subclasses

```

[Subclasses]:

    stocknn().RNN()            Recurrent Neural Networks.

    stocknn().RBF()            Radial Basis Function Networks.

    stocknn().BKP()            Back-propagation Networks.

```

## Dataset

All datasets are obtained using [pystocklib](https://github.com/mohabmes/pystocklib).

## Requirement

- Keras

- Pandas

- numpy

- scikit-learn

- matplotlib

## Credit

- PetraVidnerova