collinearity-diagnostics

There are 11 repositories under collinearity-diagnostics topic.

  • olsrr

    rsquaredacademy/olsrr

    Tools for developing OLS regression models

    Language:R102712022

  • PayThePizzo/Predictive-Analysis-Notes

    Predictive Analysis Course's notes for Computer Science B.S. at Ca' Foscari University of Venice

    Language:HTML4200

  • sduxbury/vif-ergm

    R function to detect multicollinearity in ERGM

    Language:R4010

  • vaitybharati/Assignment-05-Multiple-Linear-Regression-2

    Assignment-05-Multiple-Linear-Regression-2. Prepare a prediction model for profit of 50_startups data. Do transformations for getting better predictions of profit and make a table containing R^2 value for each prepared model. R&D Spend -- Research and devolop spend in the past few years Administration -- spend on administration in the past few years Marketing Spend -- spend on Marketing in the past few years State -- states from which data is collected Profit -- profit of each state in the past few years.

    Language:Jupyter Notebook4109

  • vaitybharati/P27.-Supervised-ML---Multiple-Linear-Regression---Toyoto-Cars

    Supervised-ML---Multiple-Linear-Regression---Toyota-Cars. EDA, Correlation Analysis, Model Building, Model Testing, Model Validation Techniques, Collinearity Problem Check, Residual Analysis, Model Deletion Diagnostics (checking Outliers or Influencers) Two Techniques : 1. Cook's Distance & 2. Leverage value, Improving the Model, Model - Re-build, Re-check and Re-improve - 2, Model - Re-build, Re-check and Re-improve - 3, Final Model, Model Predictions.

    Language:Jupyter Notebook310

  • favstats/multicol_sim

    Analyzing Multicollineaerity with a little simulation

    Language:HTML120

  • friendly/VisCollin

    Visualizing Collinearity Diagnostics

    Language:R1201

  • vaitybharati/P26.-Supervised-ML---Multiple-Linear-Regression---Cars-dataset

    Supervised-ML---Multiple-Linear-Regression---Cars-dataset. Model MPG of a car based on other variables. EDA, Correlation Analysis, Model Building, Model Testing, Model Validation Techniques, Collinearity Problem Check, Residual Analysis, Model Deletion Diagnostics (checking Outliers or Influencers) Two Techniques : 1. Cook's Distance & 2. Leverage value, Improving the Model, Model - Re-build, Re-check and Re-improve - 2, Model - Re-build, Re-check and Re-improve - 3, Final Model, Model Predictions.

    Language:Jupyter Notebook110

  • karthikvadlamani/doordash-delivery-predictions

    Prediction of delivery times for DoorDash deliveries. Performed feature engineering (creation, encoding), feature selection using (multi)collinearity analysis, Gini importance and PCA. Applied 6 ML models to perform regression analysis on delivery time prediction.

    Language:Jupyter Notebook0100

  • PatilSukanya/Assignment-05.-Multiple-Linear-regression-Q2

    Used libraries and functions as follows:

    Language:Jupyter Notebook0100

  • shwetapardhi/Assignment-05-Multiple-Linear-Regression-2

    Prepare a prediction model for profit of 50_startups data. Do transformations for getting better predictions of profit and make a table containing R^2 value for each prepared model. R&D Spend -- Research and devolop spend in the past few years Administration -- spend on administration in the past few years Marketing Spend -- spend on Marketing in t

    Language:Jupyter Notebook0100