The DPA package is the scikit-learn compatible implementation of the Density Peaks Advanced clustering algorithm. The algorithm provides robust and visual information about the clusters, their statistical reliability and their hierarchical organization.

Nested Dirichlet Process Mixture Models to characterize Built Environment Data

Non parametric Kernel Density Estimator / Classifier. Allows user to input bandwidth but does not find it. Can classify for N dimensions, but can only plot class / decision boundaries for 2.

Part III Essay

An R package for irregular histograms.

Repository for the non_param_score_est package.

Performing non-parametric Parzen Window density estimation with a Gaussian kernel, implementing the method both from scratch and using built-in functions, and compares the results across various window widths and sample sizes.