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I have a question regarding outlier detection. The dataset consists of monthly data for each location. … Also, if you have general recommendations/advice about outlier detection, please let me know as well. …

I have a question about outlier detection in my system. … Is this a good approach for outlier detection in my binary classification system? Which outlier detection techniques do you suggest in this case? Where should I put outlier detection function? …

In a blog post Andrew Gelman writes: Stepwise regression is one of these things, like outlier detection and pie charts, which appear to be popular among non-statisticians but are considered by … I understand the reference to pie charts, but why is outlier detection looked down upon by statisticians according to Gelman? Is it just that it might cause people to over-prune their data? …

Our model processes millions of multivariate observations; manual outlier detection is impractical. I am looking for a method of automatic outlier detection. … Is there another recommended R package/function/method for automatic outlier detection? …

Are anomaly detection, outlier detection and extreme event detection same or different? If different, what are the differences among them? …

I have to perform outlier detection on population estimates for certain variables at the city level. … My problem differs from a traditional outlier detection problem in two ways: If a city is an outlier, we won't be removing it from our analysis but rather we are just finding outlier cities in order to …

Can we say that the data points that lie outside the 2nd or 3rd standard deviation is an outlier? Just wanted to know can I apply this technique in outlier detection? …

However, as I can see from the histogram there is mainly 1 outlier (the rightmost) which I need to filter out. What would be the recommended outlier detection method for this data? …

I'm using Local outlier factor algorithm provided by Scikit-learn for outlier detection. … However, LOF for outlier detection does not contain this. I tried to create decision function by my self. But i'm not sure about its feasabilty. …

WHAT IS THE RIGHT WAY TO RUN OUTLIER ANALYSIS, given this scenario? Should the student run an outlier detection procedure on each variate? … Should she run an outlier detection by combining all twelve variables? But what is the logic behind this approach? …

I have to work with research paper using multivariate outlier detection methods. Please list the methods for multivariate outlier detection and give some suggestions and ideas.... …

So I am following this applied statistics class, and we were taught 5/6 tests for outlier detection and normality test, then told to apply these to some datasets. … I plotted an histogram of each dataset, and noticed that some of them were clearly not normal, so I rejected their normality with the test, and skipped outlier detection (as the tests presume the population …

I am reading a book on time series analysis and I am having problems understanding the section about outlier detection. … The authors say that when you want to know whether at a certain time $T$ there was an outlier, you should use a certain test statistic and a test with size less than $\alpha$. …

I would like to compare outlier detection algorithms. I am not sure if area under roc or under precision recall curve is the measure to use. A quick test in matlab gives me strange results. … I just wonder why so many publications recommend the AUC PR to be better suited than ROC for imbalanced datasets as their are typical for outlier detection. …

Since I have a multiclass dataset, would it make sense to use the outlier detection algorithm not for the whole dataset, but class per class? … I mean: in my case would it make sense to split the dataset in 8 partitions (one for each class), and run the outlier detection algorithm independently for each partition? …