Description: GMM-GMR is a set of Matlab functions to train a Gaussian Mixture Model (GMM) and retrieve generalized data through Gaussian Mixture Regression (GMR). It allows to encode efficiently any dataset in Gaussian Mixture Model (GMM) through the use of an Expectation-Maximization (EM) iterative learning algorithms. By using this model, Gaussian Mixture Regression (GMR) can then be used to retrieve partial output data by specifying the desired inputs. It then acts as a generalization process that computes conditional probability with respect to partially observed data.
- [CART] - data mining algorithms, K-means clusteri
- [bcm] - The Bayesian Committee Machine (BCM) is
- [EM] - Matlab language used to write the EM (Ex
- [GMM-GMR-v1.2] - This a matlab prepared using GMM algorit
- [GMM-GMR-v2.0] - Function to calculate sub-band energy(SB
- [gmm] - Bayesian mixture of Gaussians. This set
- [LWLR] - this program compare the Locally Weighte
- [TutorialonGMM-Kmean-VitebeAlgorithms] - Tutorial on GMM and KMean and Vitebe alg
- [GMM] - GMM - This code run very well and it has
- [NDA_EM_qpsk] - Using EM, expectation maximization metho
File list (Check if you may need any files):
GMM-GMR-v1.2\asd.m
............\D18.jpg
............\D22.jpg
............\demo1.m
............\demo2.m
............\demo3.m
............\EM.m
............\EM_GM.m
............\EM_init_kmeans.m
............\Fabric.0001.ppm
............\Fabric.0007.ppm
............\gaussPDF.m
............\GMR.m
............\KLD_distanceGMM.m
............\plotGMM.m
............\qwe.m
............\data\data1.mat
............\....\data2_a.mat
............\....\data2_b.mat
............\....\data3_a.mat
............\....\data3_b.mat
............\data
GMM-GMR-v1.2
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