Extreme learning machine only need to set the number of hidden nodes of the network, the algorithm execution process does not need to adjust the input weights and hidden element of bias, and only optimal solution, so it has the advantages of fast learning speed and good generalization performance. The program is used for limit learning machine classification.

ELM_MatlabClass\breast-cancer-wisconsin.data
ELM_MatlabClass\BreastTissue.xls
ELM_MatlabClass\cleveland.data
ELM_MatlabClass\computeAccuracy.m
ELM_MatlabClass\computeR2.m
ELM_MatlabClass\data_akbilgic.csv
ELM_MatlabClass\download;jsessionid=40A20D1976C7526372448EC4E906FA4B.pdf
ELM_MatlabClass\ELM-Unified-Learning.pdf
ELM_MatlabClass\ELM_MatlabClass.m
ELM_MatlabClass\example_CLASSIFICATION.m
ELM_MatlabClass\example_REGRESSION.m
ELM_MatlabClass\hepatitis.data
ELM_MatlabClass\license.txt
ELM_MatlabClass\README.md
ELM_MatlabClass

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