elasticnet-regression
There are 59 repositories under elasticnet-regression topic.
3zhang/Python-Lasso-ElasticNet-Ridge-Regression-with-Customized-Penalties
An extension of sklearn's Lasso/ElasticNet/Ridge model to allow users to customize the penalties of different covariates. Works similar to penalty.factor parameter in R's glmnet.
tsitsimis/constrainedlr
Drop-in replacement of sklearn's Linear Regression with coefficients constraints
yasarigno/Predictions_on_Energy_Consumption_in_Seattle
Prediction on energy consumptions of the city of Seattle in order to reach its goal of being a carbon neutral city in 2050.
abiasiol/VolleyballML
Machine learning applications in volleyball (python, scikit-learn)
connect-midhunr/rossmann-sales-prediction
Machine learning model to forecast the sales of each Rossmann store for any given date.
MAHMOUD2ABDALLAH/rented-bike-count
It was a competition on KAGGLE for prediction on the most sales products on bikes via their features
mayank0rastogi/MACHINE-LEARNING-ALGORITHMS
This Repository Contains Different Machine Learning and Important Concepts
ayyucedemirbas/Solar_Power_ElasticNet
ElasticNet Linear Regression on Solar Power Generation
eeshwarib23/Airbnb-regression-analysis
ML | Regression Analysis| Random Forest| XGBoost| Gradient Boost| EDA| Feature Engineering| Feature selection
faheemrajwadkar/Regularization-Techniques-for-Linear-Regression
Demonstrating Regularization techniques like Lasso, Ridge and Elastic Net to solve Linear Regression and it's relative performance with OLS
MalikHebbat/Thesis---Code
Code for Master Thesis
MathCortes/Projeto9-BostonHousing-ML_Regression
Nesse trabalho vou explorar uma conhecida base, boston dataset. Nela encontramos informações sobre algumas características de casas. Queremos estudar o comportamento dos preços desses imóveis para futuramente conseguirmos prever seus preços
niloycste/Wine-Quality-Check-using-ML-Mlflow-DVC
I constructed a machine learning model to predict the quality of wine
PiotrTymoszuk/PAH-biomarker
Analysis pipeline for the PAH biomarker study by Sonnweber T et al.
rightaway006/Penalized-regression-on-high-dimensional-data
We explored various approaches to deal with high-dimensional data in this study, and we compared them using simulation and soil datasets. We discovered that grouping had a significant impact on model correctness and error reduction. For the core projection step, we first looked at the properties of all the algorithms and how they function to come up with the best possible answer and which technique outperforms the others and why. OSCAR is a competitive regularize for classification and regression problems, with the extra capability of automatic feature aggregation, as computed and illustrated in the experiments.
sakshibabbar2019/Multiple-Linear-Regression-with-Regularization
A small project addressing a regression problem explains implementation of multiple linear regression techniques, hyperparameter tuning, collinearity, model overfitting and complexity using LASSO, Ridge and Elastic net
Saurav0129/Steel-Industry-Energy-Consumption-Prediction
The dataset used for this project is taken from the official UCI Machine Learning Repository.
Silvano315/Prediction-model-for-a-real-estate-market
This repository is the third project of the master's degree in AI Engineering that I am following. It aims toto optimize real estate price valuation through the use of advanced regularisation techniques in linear regression models by implementing Lasso, Ridge and Elastic Net in order to obtain accurate and stable price predictions.
Tynab/Machine-Learning-Overview
CyberSoft Machine Learning 03 - Overview
whonancysoni/Linear-Regression-on-Algerian-Forest-Fire-Temperature-Prediction.
Practical Implementation of Linear Regression on Algerian Forest Fire Dataset.
whonancysoni/Linear-Regression-on-Boston-Housing-Price-Prediction
Practical Implementation of Linear Regression on Boston Housing Price Prediction
yyigitturan/Baseball-Players-Salary-Prediction
This project develops a machine learning model to predict the salaries of baseball players based on their past performance.
abhijit12banerjee/AlgerianForestFires
Predict the cause of fire in the forest using different Regression Models
KasiMuthuveerappan/Jamboree-LinearRegression
📗 This repository provides an in-depth exploration of the predictive linear regression model tailored for Jamboree Institute students' data, with the goal of assisting their admission to international colleges. The analysis encompasses the application of Ridge, Lasso, and ElasticNet regressions to enhance predictive accuracy and robustness.
MJawad-AbouAleiwi/SD-TSIA204
The practical works (TP) of SD-TSIA204 - Statistics: linear models course at Télécom Paris.
Musabs2802/house-price-prediction
Building models to predict house prices for Pune, India, trained on 200 data points using multiple regression techniques
noah-andersen/ml-agricultural-census-utah
In this work we attempt to fill in the gap years for the US Agricultural Census in Utah counties. Open source data from NOAA, Agricultural Census, and BLS are used leveraging Machine Learning methods and models.
rajesvariparasa/ml-processing-pipeline-for-predicting-houseprices
This repository contains an ML workflow to predict house prices in Ames, Iowa. This project work is carried out under the Machine Learning module of the GeoDSc track of the Copernicus Master in Digital Earth.
RajKulk16/CLTV-Compass
The main objective of this project is to forecast the Customer Lifetime Value (CLTV) using user and policy data.
sai-manas/Diamond_Price_Prediction
Diamond Price Predictor - Web Application: Predict diamond prices using various regression models: Linear Regression, Lasso, Ridge, ElasticNet, Decision Tree Regressor, Random Forest Regressor, and KNeighbors Regressor. The chosen Random Forest Regressor, with a remarkable accuracy of 97%, is deployed in a user-friendly Flask app
figo2001/Regression-Project
Develop a regression project incorporating Ridge, Lasso, and Elastic Net with thorough data cleaning, exploration, and visualization for improved accuracy.
Mohshaikh23/Wine-Quality-Prediction-using-MLFlow
Wine Quality Prediction using ElasticNet Regression using MLFlows
Musabs2802/insurance-pricing-forecast
Building a regression model to predict insurance charges of customers based on features using multiple regression techniques
priyadarshighosh/Regularization
In this Repo , we got 3 types of Regularization : Ridge Regularization , Lasso Regularization and Elastic Net Regularization
Samir-Zade/ML-DiamondPricePrediction-EndtoEnd
By leveraging pipelines, artifacts, logging, EDA, exception handling, and other components, the Diamond Price Prediction project provides a robust and scalable solution for predicting diamond prices, empowering stakeholders in the diamond industry to make data-driven decisions with confidence.
sonwaneshivani/Fire-Weather-Index-Prediction
ML Regression application built using Flask