BITCOIN PRICE PREDICTION USING PYSPARK

Bitcoin Price Prediction using Spark Global and self-designed Local Model with Big data preprocessing and manipulation solution.

• Global Model: Spark build-in MLlib, model can benefit from all the data.
• Local Model: Utilize the ML algorithm from third party(eg. scikit-learn), model only can benefit from a subset of the data, but could be faster.

Prerequisites

• Packages:
  • python >= 3.8.8
  • pyspark >= 3.1.1
  • numpy >= 1.19.2
  • pandas >= 1.2.3
  • plotly >= 4.14.3
  • scikit-learn >= 0.24.1
  • statsmodels >= 0.12.2
  • pmdarima >= 1.8.2

Built With

• Spark - Lightning-fast unified analytics engine
• Python - Programming language

Files

code

• global_mode.ipynb : Global Model Prediction on Spark.
• local_LR.ipynb : Local Model design(Linear Regression) on Spark to make predictions.
• local_autoReg.ipynb : Local Model design(ARIMA/VectorARIMA) on Spark to make predictions.
• preprocess_bitcoin_pyspark.ipynb : Data imputation and resampling by big data solution(Spark).
• blockChain_crawler.ipynb : A crawler to get BlockChain Information.
• feature_engineering.ipynb : Feature Engineering, include Data combination, Label maker, financial indicators maker.
• tsCrossValidation.py : A common code for time series Cross Validation.

dataset

• bitcoin_1m_1min.csv : A subset dataset for functionality test; 1 month(03/2021) 1min interval data of bitcoin.

Paper

• conference_paper.pdf

Authors

• Chi Wang
• Luer Lyu
• Joel Ligma
• Junfeng Wang

License

This project is licensed under the MIT License - see the LICENSE file for details.
If you want to cooperate or use this project, please contact the author: [email protected]

Acknowledgments

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