n2mittal/Credit-Card-Fraud-Detection

Reproducible Machine Learning Code to detect potential Credit Card Fraud Transactions

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rijul11/Credit-Card-Fraud-Detection

Fraud Detection on Credit Transaction using Data Cleaning, Variable Creation, Feature Selection, ML Model Exploration and Selection

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robertofernandezmartinez/businesscase-python-cro-ecommerce-public

Business case (Python): CRO for an online store

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robertofernandezmartinez/businesscase-python-real-estate-airbnb-public

Business case (Python): Finding opportunities for real-estate investments on an European capital

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robertofernandezmartinez/businesscase-sql-wholesaler-public

SQL: Revenue optimization for a multinational wholesaler

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isaac2math/solarpy

subsample-order least-angle regression, a algorithm that performs quick, sparse, stable and accurate variable selection for ultrahigh dimensional data under complicated dependence structures, harsh irrepresentable conditions and high multicollinearity.

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SajedehLashgari/Risk-Factors-Affecting-Covid-19-Disease-Fatality-Rate

I collected datasets related to COVID-19 disease in various dimensions and presented them here. You can read its details in the "Adaptive Elastic-net Sliced Inverse Regression to Identify Risk Factors Affecting COVID-19" paper. Also, here is the code for the proposed method.

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adrian-io/pisa-clustered-ols

Prediction of all countries’ PISA scores with macroeconomic indicators using pooled OLS with clustered standard errors

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mjkim1001/AS21

Applied Statistics I, 2021, UNC at Chapel Hill-linear regression

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S-Soluel/STAT-172-Final-Project

Final Project: Predictive and descriptive analysis, interpretations, and recommendations based on Austin Animal Center data on cats housed at the shelter. The main focus of this analysis is to determine which factors affect a cat's chances of being adopted or returned to their owner.

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JorgeCastilloMateo/GEVSSVS

GEV-SSVS regression

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nilotpalsanyal/GWASinlps

R package for Non-local Prior Based Iterative Variable Selection for Genome-Wide Association Studies, or Other High-Dimensional Data

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lcrawlab/SINATRA_AoAS_Results

Reproducibility repo for the simulation and real data results in the SINATRA manuscript set to appear in AoAS.

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matteopelagatti/indeptest

Code and data of the paper "A nonparametric test of independence between two random variables of any kind"

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RuzhangZhao/BenchmarkHVG_old

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eyllcyldrm/MantarSiniflandirma

SVC and KNN methods were used to predict whether mushrooms are poisonous or edible according to their properties. Random forest and chi-square variable selection methods were applied and the 10-fold cross validation method was used and f1 scores were calculated by re-estimating. Finally, the models were compared.

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liangyuanhu/RR-BART

A flexible approach for variable selection in the presence of missing data

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steve303/stat420_variableSelection

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mtnbikerjoshua/jcreg

A collection of functions for checking the assumptions of linear regression and performing variable selection.

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scabras/varseldmmp

DPMP prior on model space

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weichengv/BANNs

Code and Simulations using Biologically Annotated Neural Networks (BANNs)

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weichengv/genee

A Recalibrated Hypothesis Test for SNP-Level Summary Statistics

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MinhDg00/penalized-mle-with-reparameterization

implement BCD to find l1-penalized MLE with appropriate parametrization multivariate GLM

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femtonelson/Linear-Regression-in-R

Predicting a startup's profitability with a linear regression model in R

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alaradirik/variable-selection-using-R

R script to rank and select variables based on their importance/predictive power

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elifdogandar/DataAnalysisandLinearModels-R

Exploratory data analysis, missing value imputation and linear models on carnicoma data

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uhkniazi/CCrossValidation

Class to perform cross validation and draw ROC curves for Test and Training data

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yingzima/Stock-Market-Prediction

Analysis of the Underlying Dynamics in the Stock Market: Stock Price of Southwest Airlines and Its Relationship with Other Stocks in the Market

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EhtashamBillah/Variable-Selection-By-Recursive-Feature-Elimination-RFE-

All independent variables do not have the similar impact on dependent variable. Here we will try to find the independent varibles that have most significant impact on dependent variable to make the ML algorithm fast and accurate by utilizing RFE.

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Srungeer-Simha/Logistic-Regression

Applying logistic regression to predict employee attrition and understand key contributors to attrition

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Srungeer-Simha/Linear-Regression

Applying Linear regression for car price prediction and key variable identification

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hanfu-bios/varsel

R package for generalized knockoffs filter for controlled variable selection

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aakbarie/Predicting_home_prices

Various variable selection methods are explored

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