The outlier detection problem can be defined as follows: given a dataset X, find objects that are considerably dissimilar, exceptional and inconsistent with respect to the remaining majority of ...

In my last few articles, I've looked at a number of ways machine learning can help make predictions. The basic idea is that you create a model using existing data and then ask that model to predict an ...

Reducing hurdles to clinical trials without compromising the therapeutic promises of peptide candidates becomes an essential step in peptide-based drug design. Machine-learning models are ...

If you have a set of data items, the goal of anomaly detection is to find items that are different in some way from most of the items. Anomaly detection is sometimes called outlier detection. There ...