high density region estimation
High Density Region Estimation with KernelML – Towards Data Science
KernelML is a brute force optimizer that uses parameter constraints and sampling methods to minimize a customizable loss function. The package uses a Cythonized backend and parallelizes operations across multiple cores with the IpyParallel. KernelML is now available on the Anaconda cloud and PyPi (pip). Data scientists and predictive modelers often use 1-D and 2-D aggregate statistics for exploratory analysis, data cleaning, and feature creation. Higher dimensional aggregations, i.e., 3 dimensional and above, are more difficult to visualize and understand.