Statistical pattern recognition course projects from shiraz university.

Reference implementation of the Distance-Based Boolean Applicability Domain for HTS datasets

Implementation of Kernel Density Estimation for Naive Bayes from scratch

Classification of wine quality using a hard_parzen and a soft_parzen with gaussian kernel models

Containing various ML projects, including image and text classification, clustering, regression, and neural networks. Projects include implementations of Random Forest, SVM, Decision Trees, EM algorithms, and advanced models like MLP and CNN, with datasets ranging from facial emotion detection to ECG signals and more.

Project to implement Gaussian mixture model and Parzen window estimation.

Performing non-parametric Parzen Window density estimation with a Gaussian kernel, implementing the method both from scratch and using built-in functions, and compares the results across various window widths and sample sizes.