stepwise-regression
There are 44 repositories under stepwise-regression topic.
dcajasn/Riskfolio-Lib
Portfolio Optimization and Quantitative Strategic Asset Allocation in Python
rsquaredacademy/olsrr
Tools for developing OLS regression models
talhahascelik/python_stepwiseSelection
Automated Backward and Forward Selection On Python
avinashbarnwal/stepwisereg
Stepwise Regression-Python
SebastianAment/CompressedSensing.jl
Contains a wide-ranging collection of compressed sensing and feature selection algorithms. Examples include matching pursuit algorithms, forward and backward stepwise regression, sparse Bayesian learning, and basis pursuit.
emirhankartal-py/python_bidirectional_stepwise_selection
Automated Bidirectional Stepwise Selection On Python
xiaolinmu/DamSafetyMonitoring
The effect quantity is decomposed into water pressure component, temperature component and aging component, and the diagram is made automatically. Refer to Prof. Wu Zhongru's Safety Monitoring Theory & It's Appliaction of Hydraulic Structures
nishantdhol/AgricultureForecasting
An algorithm intended to predict the yield of any crop. Used Agricultural Data sets for building the Step-wise Regression Model. Technology Stack: R language, SQL, Linear Regression library, Plumber library, Swagger API
JeffersonLab/model-selection
Model slection with stepwise regression.
Mathias-Kreis/stepwise-regression
Stepwise regression fits a logistic regression model in which the choice of predictive variables is carried out by an automatic forward stepwise procedure.
mamomen1996/Python_CS_02
Sports Analytics in Python
mamomen1996/R_CS_04
Sports Analytics in R (Step-wise Regression and Subset Selection Regression)
tboudart/Financial-Markets-Regression-Analysis
My role in this group project was to perform regression analysis on quarterly financial data to predict a company's market capitalization. I used R to develop ordinary least squares (OLS), stepwise, ridge, lasso, relaxed lasso, and elastic net regression models. I first used stepwise and OLS regression to develop a model and examine its residual plots. The plot displaying the residuals against the predicted values indicated multiplicative errors. I, therefore, took the natural log transformation of the dependent variable. The resulting model's R2 was significantly, negatively impacted. After examining scatter plots between the log transformation of market capitalization and the independent variables, I discovered the independent variables also had to be transformed to produce a linear relationship. Using the log transformation of both the dependent and independent variables, I developed models using all the regression techniques mentioned to strike a balance between R2 and producing a parsimonious model. All the models produced similar results, with an R2 of around .80. Since OLS is easiest to explain, had similar residual plots, and the highest R2 of all the models, it was the best model developed.
anupriya1519/House-Mortgage-Dataset-Analysis
Data Analysis and Decision Making Project using R
ayush-kumar-1/cs4360-project1
Data Science II Project 1 Group Ayush Kumar, Faisal Hossain, Brandon Amirouche
deeprpatel700/Regression_Analysis_-_Factors_affecting_Life_Expectancy
Statistical Multivariate Regression Analysis to determine the effects of mortality, economic and social factors on life expectancy.
mzkki25/stepwise-linear-regression-without-libraries
Tugas besar analisa data
ntdung96/RegressionAnalysis_mtcars
I took a look at the mtcars dataset in R and wanted to do an analysis on this dataset. In 2018
rafsanRubaiyat/Forest-Fire-StepwiseRegression
Forest-Fire-StepwiseRegression The relationships between the ‘Probability of Forest Fire’ in Algeria and its various weather components have been estimated.
Sarthak-Mohapatra/Classifying-Credit-Card-transactions-as-Fraudulant-or-Genuine-using-ML-Algorithms.
Classifying Credit Card transactions as fraudulent or genuine using Classification techniques.
scottherford/Barley-House
Ames Housing Prices: Advanced Regression Techniques
TheChanRProject/CGUMRAssignments
Repo for multiple regression assignments in Quant III for EDUC467.
apang782/vroom2
Regression Analysis of Used Car Prices
aryanrzn/Bayesian-Logistic-Regression-Model
This analysis is based on the multivariate normal prior
avalanche284/Bitcoin-price-prediction
Regression models for predicting bitcoin price
domenico-rgs/EFSA-Project
Statistical Learning Theory project - EFSA
Hadley-Dixon/CancerMortality
Multivariate least squares regression model that predicts cancer mortality rates for US counties
jgurakuqi/pattern-estimation-and-trend-analysis
The goal of these examples is to analyse the given datasets to determine whether some models can be established for purposes of prediction, to assess how stepwise prediction behaves with respect to a personally chosen model and determine an unknown trend in the cereal dataset.
NursultanBS/COVID19-Healthy-Diet-Prediction
Identifying the most influential food groups on COVID-19 recovery rate: exploratory data analysis and statistical modeling
PRiauwindu/Ames-Housing-Sale-Price-Prediction
Training a predictive model to forecast the house sale price in Ames, Iowa using Supervised Machine Learning Multiple Linear Regression algorithm with Stepwise Regression feature selection.
shubham199408/Colorado-ski-resort-new-homes-price-prediction-in-R
Performing EDA and building model that predicts the selling prices of new homes at a Colorado ski resort
Siddharth1989/MonthlyUtilityBillEstimation
The given dataset contains electricity consumer household information. This information has been used to predict the amount to be paid by the consumer with the help of regression model selection and validated with feature importance.
vargovema/ML_movies_votes
Classification of movie rankings
victorhxk26/world-happiness-analysis
Stepwise regression and factor analysis on world happiness data using SPSS
GLAZERadr/Stepwise_Regression
This repository contain about stepwise regression from scratch using python
lundquist-ecology-lab/Thar_Desert_water_analysis
Analysis of survey data collected by M. Weisend in the Thar Desert, India. Includes example analysis using stepwise regression and ANCOVA.