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?
Cross Validated is a question and answer site for people interested in statistics, machine learning, data analysis, data mining, and data visualization. It's 100% free, no registration required.
Here's how it works:
- Anybody can ask a question
- Anybody can answer
- The best answers are voted up and rise to the top
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.