Abstract: Outlier detection is an important problem with applications in many fields. Such applications generally process high dimensional datasets. Among the existing methods of detecting outliers, ...
1. Given noisy data with outliers. 2. Smooth data using a flat CCMA kernel for global emphasis. - Utilize a flat kernel, such as uniform, to prevent excessive focus on individual data points. - The ...
This project contains a simple example to show how a gRPC client can access an external gRPC service, with outlier detection configured to eject instances of the service when there are 5 consecutive ...
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