/Perceptually-Important-Points

PIPs

Primary LanguageJupyter NotebookMIT LicenseMIT

Perceptually-Important-Points

PIP is a method of reducing the dimensionality of timeseries data, and significantly in a way that closely follows the human method of pattern recognition.Human perception is excellent at recognizing visual patterns, and analysts can quickly identify irregularities in the data by focusing on these specific points. This algorithm hopes to mimic this behaviour by identifying the point with the largest euclidean distance from a line the passing through the first and last point of a window of interest.

Perceptually Important Points

Perceptually Important Points

Fractal Dimentianality

Fractal Dimentianality