Abstract
We collected fatigue stress concentration factor and used Support Vector Machines (SVM) by linear kernel to reduce dimension processing. In order to research the way of dimensionality reduction for data, we also processed the sample of stress fatigue concentration factor to compare with Principal Component Analysis(PCA). The results showed that the sample is processed by linear kernel could improve efficiency to train by SVM again.
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