Gradient Boosting Classifier based on Gaussian Process
碩士 === 國立臺灣大學 === 資訊管理學研究所 === 107 === Gaussian process (GP) is mainly used to solve regression and classification problems in machine learning. GP is a nonparametric model with good prediction performance and wide applications. However, GP has an obvious drawback: high time complexity. This drawbac...
| Main Authors: | , |
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| Other Authors: | |
| Format: | Others |
| Language: | en_US |
| Published: |
2019
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| Online Access: | http://ndltd.ncl.edu.tw/handle/uyjc7c |