Monitoring the performance of the web server and classification-based methods

Classification algorithms can be used to detect outliers. The ordinary strategy is to train a one-class model only for the normal data point in the training dataset. Once you set up the model, any data point that is not accepted by the model is marked as an outlier.

Monitoring the performance of the web server and classification-based methods

The OCSVM algorithm

The OCSVM (One Class SVM) algorithm projects input data into a high-dimensional feature space. Along with this process, it iteratively finds the maximum-margin hyperplane. The hyperplane defined in a Gaussian reproducing kernel Hilbert space best separates the training data from the origin. ...

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