High Density Region Estimator (HDRE) HDRE Goals 1. Approximate any empirical distribution 2. Build a parameterized density estimator 3. Outlier detection and dataset noise reduction… Read More »Use Cases For High Density Region Estimators
KernelML – Hierarchical Density Factorization The purpose, problem statement, and potential applications came from this post on datasciencecentral.com. The goal is to approximate any multi-variate distribution using… Read More »New Algorithm For Density Estimation and Noise Reduction
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… Read More »High Density Region Estimation with KernelML
I recently created a ‘particle optimizer’ and published a pip python package called kernelml. The motivation for making this algorithm was to give analysts and… Read More »Generalized Machine Learning – Kerneml – Simple ML to train Complex ML
The trend and seasonality can be accounted for in a linear model by including sinusoidal components with a given frequency. However, finding the appropriate frequency… Read More »How signal processing can be used to identify patterns in complex time series
