Feature Selection using Metaheuristics Made Easy: Open Source MAFESE Library in Python

Pearson correlation coefficient calculator

The given information of network connection, model predicts if connection has some intrusion or not. Binary classification for good and bad type of the connection further converting to multi-class classification and most prominent is feature importance analysis.

In this repository, four famous correlation algorithms have been implemented. Pearson, spearman, Chatterjee, and MIC correlation algorithm implemented

"A set of Jupyter Notebooks on feature selection methods in Python for machine learning. It covers techniques like constant feature removal, correlation analysis, information gain, chi-square testing, univariate selection, and feature importance, with datasets included for practical application.

A basic Java GUI application built with Netbeans, which is able to filter values imported from a CSV file (with a search query from the user) and find the Pearson's Correlation Coefficient from 2 columns of numerical values (the columns which are selected are hardcoded). The correlation coefficient is presented numerically with the option to vie…

Calculating the Pearson Correlation Coefficient for big data

A program that will return the Pearson correlation coefficient of the stocks entered. One coefficient is returned for each possible pair. The program will plot a heat map and will return a CSV file containing the correlation of each possible stock pair.

Movie Recommendation System with the data from MovieLens

Exploring correlations in an isobaric labeling mass spectrometry-based proteomic data set

This repository contains the solutions to HackerRank's 10 Days of Statistics.

This package contains functions to find similarities between arrays

Projects of Machine learning and Deep learning

Simple Pearson's correlation coefficient calculator.

Use PyConforMap to generate a simple scatter plot to map conformational landscapes of intrinsically disordered proteins, and quantify conformational diversity.

SUTD ISTD 2021 50.034 Introduction to Probability & Statistics 1D Project

MovieLens is a well-known database that collects movie ratings, reviews, and metadata. With the rise of streaming services and the exponential growth of content, having an effective recommendation system has become crucial for enhancing user experience. So here is our Movie Recommender System.

10 Days of Statistics Hackerrank Solutions

In this project is a programming assignment wherein you have to build a multiple linear regression model for the prediction of demand for shared bikes. You will need to submit a Jupyter notebook for the same.