CS-669 Pattern Recognition Assignment-2: The following discussion revolves around the modelling of data classifier in accordance with the bayesian decision theory. Unlike previous assignment here we do not assume class conditional probablity to be normal but instead we assume that the distribution is in the form of function that can be approximated as the linear combination of many gaussians(precisly k-gaussians).
The dataset considered here are:
It is a two dimensional speech data
It has two parts (a) This dataset set contains images which include extraction of features from the images in two forms, one would be patch representation of image and another would be Bag of Visual Words representation. (b) This dataset contains cell images on which segmentation of the region based on the intensities (data points) which are predicted using K-means and GMM clustering.