A new table has been added to the report sheet allowing you to define the optimization settings of the analysis or use the default software settings. A revamped interface will allow you to easily generate a design for response surface analysis. Response surface designs are widely used to optimize various processes, like in the food industry, for example. Response Surface Designs (available in XLSTAT Life Sciences, Quality & Premium) The ROC curve is now displayed after the confusion matrix in the case of classification. A k-fold cross-validation is added for all proposed methods (regression, binary and multi-class classification). It allows you to solve quadratic problems faster thanks to second order information. Support Vector Machine (available in all XLSTAT solutions except Basic)Ī new algorithm is integrated for SVM classification (Fan 2005). Commonly used for fraud detection and machine fault diagnosis.Īccess this feature under the Machine Learning menu. The aim is to separate data into two classes (based on a decision function): the positive one, considered as the class of inliers, and the negative one, considered as the class of outliers. The One-class Support Vector Machine (One-class SVM) algorithm seeks to envelop underlying inliers. One-class Support Vector Machine (available in all XLSTAT solutions except Basic) XLSTAT 2021.1 is now available! What’s new?
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