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I have a set of points in a matrix of size 100 x 100(total 10000 points). I know that there are roughly 500 anomaly points in it. There is a corresponding truth file which contains the true anomalous points which is not available while building the algorithm. The goal is to maximize the F-measure of the anomalies returned. How do I approach this problem?

The dataset of all points

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To find the outliers you could use an outlier detection algorithm like Local Outlier Factor. This algorithm computes a score for each data point, so that you could treat the 500 objects with the highest score as an outlier.

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