In search of fast and good classification algorithm of thermostable proteins is an important issue. The Hurst exponent was able to analysis and description in fractal time series. Besides, the Support Vector Machine (svm) has advantage of high-precision and high-speed in classified the difference category data. In this study,we assay to classifying the non-symbolic sequence of the thermostable proteins by using Hurst exponent and SVM Classifier. A thermostable proteins data set with two classes was obtained from the Protein Data Bank (PDB). The sample included 40 instances, 20 instances are thermostable,and the other 20 instances are mesophilic proteins. Computing the Hurst exponent of each non-symbolic sequences of the proteins, we can obtained four feathres represented as hurst exponents respectively in each sequences of the protein. These data with four features of Hurst exponent is applied to evaluate the performances of the SVM algorithm by using 5-fold and Leave-one-out Cross-Validation method to compute the accracies of the response category variable. The research result showed this method to be able effective to carry on the high temperature protein the classification.
