stepwise-regression
There are 4 repositories under stepwise-regression topic.
- Riskfolio-Lib
dcajasn / Riskfolio-Lib
Portfolio Optimization and Quantitative Strategic Asset Allocation in Python
portfolio-optimizationconvex-optimizationstepwise-regressionduration-matchingdrawdown-modelsharpe-ratiotradinginvestmentfinanceasset-allocationprincipal-components-regressioncvar-optimizationcvxpyrisk-parityrisk-contributionrisk-factorsportfolio-managementinvestment-analysisquantitative-financeefficient-frontierLanguage:C++ 2671 - olsrr
rsquaredacademy / olsrr
Tools for developing OLS regression models
Language:R 100 talhahascelik / python_stepwiseSelection
Automated Backward and Forward Selection On Python
Language:Python 60- Language:Jupyter Notebook 28
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.
Language:Julia 27emirhankartal-py / python_bidirectional_stepwise_selection
Automated Bidirectional Stepwise Selection On Python
Language:Python 8nishantdhol / 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
Language:R 5JeffersonLab / model-selection
Model slection with stepwise regression.
Language:R 4- 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.
Language:Python 3 mamomen1996 / Python_CS_02
Sports Analytics in Python
Language:HTML 2Sports Analytics in R (Step-wise Regression and Subset Selection Regression)
Language:HTML 2tboudart / 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.
akmalmzkki / stepwise-linear-regression-without-libraries
Tugas besar analisa data
Language:Jupyter Notebook 1anupriya1519 / House-Mortgage-Dataset-Analysis
Data Analysis and Decision Making Project using R
Language:R 1ayush-kumar-1 / cs4360-project1
Data Science II Project 1 Group Ayush Kumar, Faisal Hossain, Brandon Amirouche
Language:R 1deeprpatel700 / Regression_Analysis_-_Factors_affecting_Life_Expectancy
Statistical Multivariate Regression Analysis to determine the effects of mortality, economic and social factors on life expectancy.
Language:R 1ntdung96 / 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 โProbability of Forest Fireโ in Algeria and its various weather components have been estimated.
Language:JavaScript 1Sarthak-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
Language:SAS 1TheChanRProject / CGUMRAssignments
Repo for multiple regression assignments in Quant III for EDUC467.
aryanrzn / Bayesian-Logistic-Regression-Model
This analysis is based on the multivariate normal prior
Language:R 0avalanche284 / Bitcoin-price-prediction
Regression models for predicting bitcoin price
Language:R 0domenico-rgs / EFSA-Project
Statistical Learning Theory project - EFSA
Language:MATLAB 0jgurakuqi / 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.
Language:HTML 0NursultanBS / COVID19-Healthy-Diet-Prediction
Identifying the most influential food groups on COVID-19 recovery rate: exploratory data analysis and statistical modeling
Language:HTML 0- Price-Prediction-Airbnb-MIlan-Apartments
peterhontaru / Price-Prediction-Airbnb-MIlan-Apartments
๐ What's an appropriate price? Predicting Milan's apartment prices.
Language:R 0 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.
Language:Jupyter Notebook 0Qian-Yu-2020 / Experimental-Design-and-Regression-Analysis
SPSS statistical software package. Includes Hypothesis Testing, Multiple Comparison Tests, and Interaction in Regression
0shubham199408 / 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
Language:R 0Siddharth1989 / 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.
Language:Jupyter Notebook 0vargovema / ML_movies_votes
Classification of movie rankings
Language:R 0- Language:HTML
datajudy20 / lifespan
:earth_asia: ์ ์ง๊ตญ ์ฌ๋ถ์ ๋ฐ๋ฅธ ๊ธฐ๋์๋ช ์์ธก ํ๋ก์ ํธ - ํ๊ทํด์ ๊ฐ์
Language:Jupyter NotebookGLAZERadr / Stepwise_Regression
This repository contain about stepwise regression from scratch using python
Language:Jupyter Notebooklundquist-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.
Language:R
