🚀Implementation of Logistic Regression and Linear Regression in Python for Classification Problems🏗
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Updated
Jul 23, 2020 - Jupyter Notebook
🚀Implementation of Logistic Regression and Linear Regression in Python for Classification Problems🏗
A lightweight Julia package for eQTL genome scans near real-time.
Small signal stability repository to raise awareness about interarea oscillations and provide general information and examples for their study.
This project involves analysing a dataset, estimate parameters in an empirical relationship and make inferences based on model diagnostics using R programming language.
This repo contains code to create a simple Linear Regression model in 3 different ways: 1) Python - using statsmodels 2) Python - using sklearn and 3) R using the linear model (lm) function. This code demonstrates how each method returns the same variable coefficients, p-values and other valuable test statistics.
Project for logistics exam: Resolution of a linear problem using AMPL
The MATLAB code written in the 3 files correspond to fitting linear models/testing the fitted model with independent datasets and Principal Component Analysis on Imported Datasets written in MATLAB. Each of the 3 files were written in accordance to assignment specifications
Inference in the linear model: confidence intervals for individual regression coefficients
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