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International Journal for Research Trends and Innovation
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ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Impact Factor : 8.14
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| Paper Title: | Combining Feature Selection and Deep Learning for Precise COVID-19 Cases Forecasting: A Hybrid Approach |
| Authors Name: | Rohith R , Kavipriya S , Joshua Dayalan M |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJRTI_188498
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| Published Paper Id: | IJRTI2311058 |
| Published In: | Volume 8 Issue 11, November-2023 |
| DOI: | https://doi.org/10.5281/zenodo.10259171 |
| Abstract: | Accurately predicting the number of new COVID-19 cases is crucial for informing public health policy and resource allocation decisions. In this study, we propose a hybrid approach for COVID-19 cases prediction using Light Gradient Boosting Machine (LightGBM) for feature selection with Optuna hyperparameter tuning and Long Short-Term Memory (LSTM). We use a multivariate time series dataset consisting of variables related to COVID-19 in India. We use LightGBM for feature selection and the selected features are used as input to the LSTM model. We use Optuna to tune the hyperparameters of LightGBM and evaluate the performance of our hybrid model using metrics like mean absolute percentage error (MAPE) and r-squared score(R2). Our experimental results show that our hybrid model outperforms both LSTM and LightGBM models individually and other similar combinations of feature selector algorithm and predictor models in terms of prediction accuracy. Specifically, our hybrid model achieves a MAPE of 0.87 on the test dataset. The selected features also provide insights into the most relevant factors for predicting COVID-19 cases in India. |
| Keywords: | LSTM, LightGBM, COVID-19, Feature Selection, Forecasting, Healthcare. |
| Cite Article: | "Combining Feature Selection and Deep Learning for Precise COVID-19 Cases Forecasting: A Hybrid Approach", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.8, Issue 11, page no.419 - 434, November-2023, Available :http://www.ijrti.org/papers/IJRTI2311058.pdf |
| Downloads: | 000205184 |
| ISSN: |
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
| Publication Details: |
Published Paper ID: IJRTI2311058
Registration ID:188498
Published In: Volume 8 Issue 11, November-2023
DOI (Digital Object Identifier): https://doi.org/10.5281/zenodo.10259171
Page No: 419 - 434 Country: Chennai, Tamilnadu, India Research Area: Computer Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2311058 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2311058 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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