residual-analysis
There are 0 repository under residual-analysis topic.
ChaitanyaC22 / Car-Price-Prediction-Model-for-an-automobile-consulting-company
The goal of this project is to build multiple linear regression models for the prediction of car prices.
Language:Jupyter Notebook 3vaitybharati / 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 Notebook 3Multi-Linear-Reg
Language:Jupyter Notebook 3Supervised-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 Notebook 3ashishyadav24092000 / Residual-Analysis-in-Linear-Regression
Residual analysis in Linear regression is based on examination of graphical plots which are as follows :: 1. Residual plot against independent variable (x). 2. Residual plot against independent variable()y. 3. Standardize or studentized residual plot 4. Normal probability plot
Language:Jupyter Notebook 2chinmayeeguru / Bike-Sharing-Linear-Regression-Model
To model the demand for shared bikes with the available independent variables
Language:Jupyter Notebook 1ericksonl / SleepData
📊⚙️ Using 7 years of my sleep data, this project predicts Sleep Quality using a linear regression model based on predictors such as time in bed, time asleep, temperature, alarm, and steps.
Language:R 1MoinDalvs / Learn_Multi_Linear_Regression
Prediction of Miles per gallon (MPG) Using Cars Dataset
Language:Jupyter Notebook 1tommykwok722 / Residual-Analysis-on-Regression-Models
A MATLAB program related to Regression Models
Language:Jupyter Notebook 1UdeshikaDissa / Logistic-Regression_Analysis-of-Categorical-Data
Predicting the Likelihood of Diabetes Using Common Signs and Symptoms - About one-third of patients with diabetes do not know that they have diabetes according to the findings published by many diabetes institutes around the world. Detecting and treating diabetes patients at early stages is critical in order to keep them healthy and to ensure their quality of life is not compromised. Early detection will also help to mitigate the risk of serious complications like heart disease & stroke, blindness, limb amputations, and kidney failures as a result of diabetes. The data set consists of signs and symptoms of 516 newly diabetic or would be diabetic patients, who presented at Sylhet Diabetes Hospital in Sylhet, Bangladesh. The data had been collected using the direct questionnaires method at the hospital under the supervisor of Doctors. The Source for the data set is the UCI Machine Learning Repository at, https://archive.ics.uci.edu/ml/datasets/Early+stage+diabetes+risk+prediction+dataset. The data set has 16 descriptive features and one target feature. This study intends to build a logistic regression model to predict the likelihood of having diabetes using common signs and symptoms presented by patients. A successful model will enable early detection of diabetes through signs and symptoms shown by possible patients. This study consists of two phases: 1) Phase I - preprocess and explore the data set in order to make it ready to consume for model development. 2) Phase II - build a logistic regression model to predict the likelihood of having diabetes based on signs and symptoms. The Phase I part has already been completed under previous work/submission and this report intends to cover the work carried out for Phase II. All the activities have been performed in the R package and the report has been compiled using R-Markdown.
Language:HTML 1Supervised-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 Notebook 1Jhay001 / EDA-And-Sales-Prediction-using-SLR
The "Advertising Impact Analysis" project aims to analyze the relationship between advertising expenditure across different channels (such as TV, radio, online) and its impact on sales or revenue.
Language:HTML 0PatilSukanya / Assignment-05.-Multiple-Linear-regression-Q2
Used libraries and functions as follows:
Language:Jupyter Notebook 0priya-aggarwal27 / Linear-Regression
A boat-sharing system is a service in which boats are made available for city tour. Required to model the demand for open boats with the available independent variables. It will be used by the management to understand how exactly the demands vary with different features. They can accordingly manipulate the business strategy to meet the demand levels and meet the customer's expectations. Further, the model will be a good way for management to understand the demand dynamics of a new market.
Language:Jupyter Notebook 0shwetapardhi / 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 Notebook 0Szymex49 / Life_expectancy_and_education-regression_model
The goal of the report was to fit the linear regression model to the data and check whether the data met the assumptions of the model. The results were used to make predictions.
Language:Jupyter Notebook 0hamk-uas / HAMK_Smart_City_anomaly
Anomaly detection for building HVAC data.
Language:Jupyter NotebookJaewonSon37 / Data_Analysis_and_Regression1
Practices and Assignments from the Data Analysis and Regression Class
Language:RTopic : Predicting Medal Counts by Countries in Upcoming Olympics Games // # Integrated historical Olympic data with demographic, health, and economic datasets to generate a large dataset # Developed a linear regression model displaying prediction accuracy close to 70%, within the margin of error
Language:Rmanasik29 / Simple-Linear-Regression-Newspaper-Data
Feasibility of staring a Sunday edition for a large Metroplitan newsapaper
Language:Jupyter Notebooknlawira / india-house-rent-prediction
This repository contains a project I completed for an NTU course titled CB4247 Statistics & Computational Inference to Big Data. In this project, I applied regression and machine learning techniques to predict house prices in India.
Language:Jupyter Notebooknsb700 / time-series-forecasting
Time Series Forecasting
Language:Jupyter Notebook