Hi!  I have a data set consisting of a csv-file with three columns with numerical data. I have performed my own implementation that clusters the data set with K-means and then calculates outliers based on euclidean distance between data points and the cluster centroids.  I wan't to perform the same kind of operation in Splunk but have not been successfull so far.  I have tried local outlier factor, with the following query in search:  source="dataset.csv" | fit LocalOutlierFactor 0,1,2 | search isOutlier="1.0" However, the result from this search is very poor since very few outliers are detected. The data set is labeled making it easy to see correctly classified outliers.  I have also tried with "Detect numeric outliers" from the machine learning toolkit but there, I can only chose one field to analyze and I have three fields.    Is there an optimal solution to the problem of finding outliers in this type of dataset?    Thanks in advance! ... View more