支持向量机模型用于预测分析效果显著，它在解决小样本、非线性及高维模式识别中表现出许多特有的优势，并能够推广应用到函数拟合等其他机器学习问题中-Support vector machine model is used to predict significant effect in solving small sample, nonlinear and high dimensional pattern recognition exhibit many unique advantages, and

基于最小二乘支持向量机的模式识别，特征向量为滚动轴承的能量百分比和峭度系数-Pattern recognition based on least squares support vector machine (SVM), the percentage of energy eigenvector for rolling bearing and kurtosis coefficient