Implementing the DTW (dynamic time warping), K-means, GMM and GMR on th set of Trajectories (X,Y,Z)

In the project, I have the 6 trials of the data (Trajectory (X, Y, Z-axis)). On this data I want to implement the DTW (to remove the temporal distortion), then K-means (clustering the data), then using the Mean and covariances of the K-means as the initial values for the Expectation-Maximization (EM algorithm), which learns a GMM from the data.

The output of the GMM (sub-population means and covariances which constitutes the model of the task. Given a time vector, as an input, Gaussian Mixture Regression (GMR) is used on this model to extract the set of corresponding trajectory (X, Y, Z)

Taidot: Algoritmi, C++ -ohjelmointi

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Tietoa työnantajasta:
( 0 arvostelua ) Delhi, India

Projektin tunnus: #26523109

1 freelanceria on tarjonnut keskimäärin %project_bid_stats_avg_sub_23% %project_currencyDetails_sign_sub_24% tähän työhön


I have good experience in data mining. I will be able complete your, but I just need some details. If you reply me in chat, we shall discuss.

₹1500 INR 6 päivässä
(0 arvostelua)