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grt - gesture recognition toolkit

  •    C++

The Gesture Recognition Toolkit (GRT) is a cross-platform, open-source, C++ machine learning library designed for real-time gesture recognition. Classification: Adaboost, Decision Tree, Dynamic Time Warping, Gaussian Mixture Models, Hidden Markov Models, k-nearest neighbor, Naive Bayes, Random Forests, Support Vector Machine, Softmax, and more...

K-Nearest-Neighbors-with-Dynamic-Time-Warping - Python implementation of KNN and DTW classification algorithm

  •    Jupyter

When it comes to building a classification algorithm, analysts have a broad range of open source options to choose from. However, for time series classification, there are less out-of-the box solutions. I began researching the domain of time series classification and was intrigued by a recommended technique called K Nearest Neighbors and Dynamic Time Warping. A meta analysis completed by Mitsa (2010) suggests that when it comes to timeseries classification, 1 Nearest Neighbor (K=1) and Dynamic Timewarping is very difficult to beat [1].

soft-dtw - Python implementation of soft-DTW.

  •    Python

Python implementation of soft-DTW. The celebrated dynamic time warping (DTW) [1] defines the discrepancy between two time series, of possibly variable length, as their minimal alignment cost. Although the number of possible alignments is exponential in the length of the two time series, [1] showed that DTW can be computed in only quadractic time using dynamic programming.

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