Hi,

I am a beginner of Machine Learning. These days, I tried a anomaly detection project by myself. I am confused on model selection. Since after I clean my main data(In one table I have 4 columns data all of them need find the outlier - > features = 4.). However, when I tried to fit the data with the density estimation model I find I can’t. Since after I plot a scatter of them, I find each of them shows a linear relationship, and they have very high correlation. It’s not contain cluster, just linear with some very obvious outliers.

Dose anyone can provide me some suggestions which model should I need to use on this symptom? Since I only know how to use density estimation. I want to try classification before, but it’s unsupervised(I only have those four columns, I think it may unsupervised, but I am not sure). I finished the ML course yesterday, so I am not very familiar with all of them, I am not sure. Dose any one can help me? Thank you so much~

language: python

Unsupervised Learning, Recommenders, Reinforcement

Supervised ML: Regression and Classification

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