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Improved Extreme Learning Machine based on the Sensitivity Analysis
| Content Provider | Scilit |
|---|---|
| Author | Cui, Licheng Zhai, Huawei Wang, Benchao Qu, Zengtang |
| Copyright Year | 2018 |
| Description | Journal: Iop Conference Series: Materials Science and Engineering Extreme learning machine and its improved ones is weak in some points, such as computing complex, learning error and so on. After deeply analyzing, referencing the importance of hidden nodes in SVM, an novel analyzing method of the sensitivity is proposed which meets people's cognitive habits. Based on these, an improved ELM is proposed, it could remove hidden nodes before meeting the learning error, and it can efficiently manage the number of hidden nodes, so as to improve the its performance. After comparing tests, it is better in learning time, accuracy and so on. |
| Related Links | https://iopscience.iop.org/article/10.1088/1757-899X/320/1/012015/pdf http://iopscience.iop.org/article/10.1088/1757-899X/320/1/012015/pdf |
| ISSN | 17578981 |
| e-ISSN | 1757899X |
| DOI | 10.1088/1757-899x/320/1/012015 |
| Journal | Iop Conference Series: Materials Science and Engineering |
| Issue Number | 1 |
| Volume Number | 320 |
| Language | English |
| Publisher | IOP Publishing |
| Publisher Date | 2018-03-05 |
| Access Restriction | Open |
| Subject Keyword | Journal: Iop Conference Series: Materials Science and Engineering Industrial Engineering Extreme Learning Learning Machine |
| Content Type | Text |
| Resource Type | Article |
