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Bitcoin Financial Forecasting
| Content Provider | Scilit |
|---|---|
| Author | Jain, Dhyanendra Jain, Ashu Pandey, Amit Kumar Kumar, Jogender |
| Copyright Year | 2021 |
| Description | Journal: Iop Conference Series: Materials Science and Engineering Bitcoin is one of the crypto currencies and is most unpredictable currencies. In the world of crypto currencies, the value of a coin can unpredictably upgrade or degrade. In this study, the model has been trained to predict the value of Bitcoin in USD at any given time stamp. For this prediction, three algorithms of machine learning - Linear Regression (LR), Support Vector Regression (SVR) and Neural Network Regression (NNR) have been used. The model is trained using the collected dataset. After the collection of data set, we first applied SVR algorithm, then we used LR and then NNR to calculate the error compared to the actual value. Root mean squared error (RMSE) is used as the predictive measure. Out of the three algorithms, LR was found out to be more accurate for predicting the value of bitcoin. |
| Related Links | https://iopscience.iop.org/article/10.1088/1757-899X/1049/1/012003/pdf |
| ISSN | 17578981 |
| e-ISSN | 1757899X |
| DOI | 10.1088/1757-899x/1049/1/012003 |
| Journal | Iop Conference Series: Materials Science and Engineering |
| Issue Number | 1 |
| Volume Number | 1049 |
| Language | English |
| Publisher | IOP Publishing |
| Publisher Date | 2021-01-01 |
| Access Restriction | Open |
| Subject Keyword | Journal: Iop Conference Series: Materials Science and Engineering Hardware and Architecture |
| Content Type | Text |
| Resource Type | Article |
