Evaluate the Buy Online Pick-up in Store (BOPS) strategy with a real-world dataset
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Updated
Apr 19, 2018
Evaluate the Buy Online Pick-up in Store (BOPS) strategy with a real-world dataset
Recipes for common linear regression operations: model comparisons, heteroskedasticity, collinearity, goodness of fit
A real estate company that has a dataset containing the prices of properties in the Delhi region. It wishes to use the data to optimise the sale prices of the properties based on important factors such as area, bedrooms, parking, etc
Car Price Prediction : Predictions made by using linear regression aaproach
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 y…
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. Levera…
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-buil…
This is an linear approach machine learning model used to predict the values of variable(dependent) based on other variables(independent).
Ordinary least square (OLS) regression analysis carried out in this project. The selected dependent variables are some public health indicators like anxiety, diabetes. We tried to find the independent variables which are responsible for this health hazard.
tool to verify model test specifications and presence of heteroscedasticity in the forest inventory plot
Used libraries and functions as follows:
GWAS of trait variance (C++)
R package to perform regression-based Brown-Forsythe test
This instruction aims to reproduce the results in the paper “Calibration of inexact computer models with heteroscedastic errors” proposed by Sung, Barber, and Walker (2022).
Skript zur Videoreihe Regressionsdiagnostik in R
OLS Bootstrap on Cross-Sectional Data
Traditional Regression problem project in Python
Estimation of the Hubble constant using Gaussian process regression and viable alternatives
time series analysis in R use cases
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