GitHub topics: variance-inflation-factor
aneeshmurali-n/ML-Turbine-Energy-Yield-Prediction-for-Gas-Turbine-Optimization
This project uses machine learning to predict Turbine Energy Yield (TEY) from gas turbine data, optimizing settings to improve energy output, reduce fuel consumption, and cut costs. TEY predictions help detect deviations from normal operations, signaling potential turbine issues like degradation.
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VivekSagarSingh/Probability-of-Credit-card-Default
Classification problem using multiple ML Algorithms
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KasiMuthuveerappan/IVY_League-Admission-LinearRegression
📗 This repository provides an in-depth exploration of the predictive linear regression model tailored for Jamboree Institute students' data, with the goal of assisting their admission to international colleges. The analysis encompasses the application of Ridge, Lasso, and ElasticNet regressions to enhance predictive accuracy and robustness.
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marinafajardo/prevendo-customer-churn
Prevendo Customer Churn em Operadoras de Telecom
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anik475/Kaggle-Challenge-Campaign-Contributions-in-the-United-States
This assignment contain information on the contributions to the campaigns of the US politicians at the state and the federal level. The contribution data has been collected from various sources and covers the 1989-2017 period
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Niteshchawla/Jamboree-LinearRegression
Analysis will help Jamboree in understanding what factors are important in graduate admissions and how these factors are interrelated among themselves. It will also help predict one's chances of admission given the rest of the variables.
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Rakhi-TS22/Insurance_Charges
Insurance charges calculation
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saikrishnabudi/Multi-Linear-Regression
Data Science - Multi Linear Regression Work
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madisongarccia/STAT330
R programming - Statistical Modelling II
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venkatesh-eranti/Housing_case-study
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
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NicholasDominic/Stochastic-VIF-ID-Rice-SNPs
By leveraging ensemble learning, this program can be used to analyze the Linkage Disequilibrium between SNPs in each Indonesian rice chromosomes. Developed using Python 3.9.12.
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hanfei1986/Dimension-reduction-by-dropping-high-VIF-features-recursively
This Jupyter notebook demonstrates a dimension reduction method by dropping high variance-inflation-factor (VIF) features recursively.
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DandiMahendris/regression-model-cac
Regression models for predicting customer acquisition costs (CAC) and the effectiveness of univariate and lasso feature selection techniques in improving the accuracy.
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garimagupta123/LeadScore_LogisticRegression_Assignment
Logistic regression model build on lead score data to score leads on the basis of their probability of conversion.
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SharadChoudhury/Bike-Sharing-prediction
Multiple Regression model building with Sklearn and statsmodels and analysis of relevant predictors using P-values and VIF
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shanuhalli/Assignment-Multi-Linear-Regression
Prepare a prediction model for profit of 50 startups data and Consider only the some columns and prepare a prediction model for predicting Price.
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rochitasundar/Regression-dynamic-price-prediction-ReCell
The objective is to build a ML-based solution (linear regression model) to develop a dynamic pricing strategy for used and refurbished smartphones, identifying factors that significantly influence it.
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hkalager/ML_AccountingFraud
This repository includes the scripts to replicate the results of my WORKING paper entitled "A Machine Learning Approach to Detect Accounting Frauds". You can access a copy of the manuscript at https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4117764
Language: Python - Size: 22.8 MB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 6 - Forks: 3
sauhard2701/Fraud-Transaction-Detection
INSAID Assignment to create a ML model to detect fraud transactions for a financial company.
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MoinDalvs/Learn_Multi_Linear_Regression
Prediction of Miles per gallon (MPG) Using Cars Dataset
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abduliante/vehicle-default-loan-prediction
Forecasting the likelihood of a customer defaulting their auto loan using classification models
Language: Python - Size: 69.7 MB - Last synced at: 6 days ago - Pushed at: over 3 years ago - Stars: 2 - Forks: 1
rochitasundar/Classification-booking-cancelation-prediction-StarHotels
The aim is to develop an ML- based predictive classification model (logistic regression & decision trees) to predict which hotel booking is likely to be canceled. This is done by analysing different attributes of customer's booking details. Being able to predict accurately in advance if a booking is likely to be canceled will help formulate profitable policies for cancelations & refunds.
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