adjusted-r-squared
There are 9 repositories under adjusted-r-squared topic.
stefmolin/ml-utils
Machine learning utility functions and classes.
kaur-anupreet/boston-housing-price-prediction
Predicted house prices using multiple linear regression. Used back elimination to further improve the model and select features based on p-value and adjusted R squared value.
caralifarrell/Beginner-Machine-Learning-in-Python-ChatGPT-Bonus-2023
An introduction into the world of machine learning with a comprehensive Udemy online course, designed for beginners, to learn Python programming fundamentals and gain valuable insights into the practical applications of machine learning.
anthonyli01/Regression-Model-for-Car-Prices
University Project: using linear regression models to predict secondary market car prices based on a series of features. We will apply variable selection techniques and optimisation in attempt to build the best predictive model.
devosmitachatterjee2018/Linear_Statistical_Models
The project involves the multivariate regression analysis of a dataset.
Hermann-web/some-common-statistical-methods
python module, showcasing computation (as part of a learning process) of some common statistical methods including mininum sample size, confidence interval estimation methods for mean or proportion, hypothesis testing mehods and regression models witth metrics and test suites
vikhyatnegi/Linear-Regression-
This assignment is a programming assignment wherein you have to build a multiple linear regression model for the prediction of demand for shared bikes.
PBPatil/Regression-Projects
Regression is one of the foundational techniques in Machine Learning. Being one of the most well-understood algorithms, beginners always struggle to understand some fundamental terminology related to regression. In this series of projects, I will try to give you basic ideas of underlying concepts with the help of practical examples. If you are starting your career or want to brush up on your knowledge of regression, this repo is made up for you. These projects begins by introducing some simple real-life examples for regression. From a brief introduction to most of the concepts used in regression to hands-on experience, these projects will give you enough understanding to apply those in real-world problems. With the help of the background developed, you will code your regression model in python.