Finding out the most relevant features for pricing of a house

SCFGP: Sparsely Correlated Fourier Features Based Gaussian Process

Builds a sparse covariance matrix given a set of model parameter locations (x,z), and a correlation kernel

How does PCA work?

Homework and assignments for ENPM 673

Penalized precision matrix estimation via block-wise coordinate descent (graphical lasso)

This repository contains exercises from the Machine Learning course.

Perform Principal component analysis and perform clustering using first 3 principal component scores (both heirarchial and k mean clustering(scree plot or elbow curve) and obtain optimum number of clusters and check whether we have obtained same number of clusters with the original data (class column we have ignored at the begining who shows it …

Testing equality of variance and covariance matrix

Python ML/AI repository

FIFA'19 datasets Analysis

Code for the paper E. Raninen and E. Ollila, "Bias Adjusted Sign Covariance Matrix," in IEEE Signal Processing Letters, vol. 29, pp. 339-343, 2022, doi: 10.1109/LSP.2021.3134940.

Forecasting time series data using ARIMA models. Used covariance matrix to find dependencies between stocks.

This repository is a comprehensive archive of projects and assignments undertaken for the Pattern Recognition course (TIP8311) at the Federal University of Ceará as part of my Master's curriculum.

Penalized precision matrix estimation

This is an implementation of a custom-trained face detection classifier using the Viola Jones Algorithm cascaded with an Eigen Face recognition system based on Principal Component Analysis.

Contains some Test of Statistics