Research Article
Using a Selective Ensemble Support Vector Machine to Fuse Multimodal Features for Human Action Recognition
| Input: | Training set , verification set , base classification algorithm SVM, number of base classifiers , number of selected base classifiers | Output: | Selected base classifier set | Training process: | (1) Initialize the base classifier set | (2) For | (3) Based on the training set , a new training set is obtained by using Bootstrap random sampling method | (4) The base classifier is trained on the training set by using the base classification algorithm and added to the set | (5) End for | (6) Selecting process: | (7) Each base classifier is tested on verification set and its output is obtained | (8) The selected base classifier set is obtained by using CCCSA | |
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