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Download CatBoost For Big Data An Interdisciplinary Review by ['Nguyễn Hữu Trí'] in PDF format completely FREE. No registration required, no payment needed. Get instant access to this valuable resource on PDFdrive.to!
About CatBoost For Big Data An Interdisciplinary Review
This document provides an interdisciplinary review of research on CatBoost, a gradient boosted decision tree algorithm, for big data applications. It summarizes key findings from several studies on CatBoost's performance for classification and regression tasks on heterogeneous versus homogeneous data. For heterogeneous data problems, CatBoost generally performed well and was better suited than alternatives like neural networks. However, for homogeneous data, deep learning methods sometimes outperformed CatBoost in terms of accuracy. The document also notes that CatBoost's training time performance versus other algorithms like XGBoost was mixed in different studies, which may be due to its sensitivity to hyperparameter settings.
Detailed Information
| Author: | ['Nguyễn Hữu Trí'] |
|---|---|
| Publication Year: | 2021 |
| Pages: | 45 |
| Language: | English |
| Format: | |
| Price: | FREE |
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