My target variable is boolean and has 0.001% of NO records and remaining YES records. Can anyone suggest algorithms which are best for anomaly detection in R when there is severe class imbalance.

  • $\begingroup$ What's an "anomaly" here? A "No" where you'd expect a "Yes" and vice-versa? $\endgroup$ – Spacedman Aug 25 '16 at 16:54
  • 1
    $\begingroup$ anomaly here is occurrence of "No" when you would expect "Yes" to happen $\endgroup$ – alily Aug 26 '16 at 10:22
  • $\begingroup$ Anomaly detection algorithms are mostly intended to be used with an imbalanced data set. By definition, an anomaly is something unusual, and you typically don't train a discriminator, but some estimate of probability density for non-anomalies. $\endgroup$ – Neil Slater Sep 23 '16 at 21:23
  • $\begingroup$ So you basically want to predict if it is a YES or a NO? $\endgroup$ – Pieter Aug 7 '17 at 6:11

Here is a pretty detailed summary on Handling Imbalanced Classes. Since you mentioned R, you might want to take a look at unbalanced package.

| improve this answer | |

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Not the answer you're looking for? Browse other questions tagged or ask your own question.