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Model Combination Schemes in ML by AROCKIA PRINCE is a document available to read on EtoBox.

The document discusses various model combination schemes for multiple base-learners, focusing on multiexpert and multistage methods. Multiexpert methods include global approaches like voting and stacking, as well as local approaches such as mixture of experts, while multistage methods employ a serial approach to train base-learners based on the accuracy of previous ones. The final output is generated by combining predictions from these base-learners, often selecting the maximum value in classification tasks

Author
AROCKIA PRINCE
Language
EN