WaveletML
Wavelet Decomposition Based Hybrid Machine Learning Models
Wavelet decomposes a series into multiple sub series called detailed and smooth components which helps to capture volatility at multi resolution level by various models. Two hybrid Machine Learning (ML) models (Artificial Neural Network and Support Vector Regression have been used) have been developed in combination with stochastic models, feature selection, and optimization algorithms for prediction of the data. The algorithms have been developed following Paul and Garai (2021) doi:10.1007/s00500-021-06087-4.
- Version0.1.0
- R versionunknown
- LicenseGPL-3
- Needs compilation?No
- Last release04/05/2023
Team
Mr. Sandip Garai
Dr. Ranjit Kumar Paul
Show author detailsRolesAuthorDr. Md Yeasin
Show author detailsRolesAuthor
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Last 30 days
This package has been downloaded 157 times in the last 30 days. Now we're getting somewhere! Enough downloads to populate a lively group chat. The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 9 times.
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Last 365 days
This package has been downloaded 1,948 times in the last 365 days. Now we’re talking! This work is officially 'heard of in academic circles', just like those wild research papers on synthetic bananas. The day with the most downloads was Aug 21, 2024 with 27 downloads.
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Dependencies
- Imports12 packages
- Reverse Imports1 package