smote

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Here are 18 public repositories matching this topic...

igarleni / Imbalanced-Data-analysis-with-R---First-steps

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Learning how to analyze imbalanced Data, implementing SMOTE and using unbalanced R package

data-science data-mining r data-mining-algorithms imbalanced-data smote

Updated Feb 28, 2017
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shoaib555 / Choosing-preferable-mode-of-transport-by-employees

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The project involves deciding on the mode of transport that the employees prefer while commuting to office. For this, multiple models such as KNN, Naive Bayes, Logistic Regression have been created and explored to check their model performance metrics. Bagging and Boosting modelling procedures have also been applied to create the models.

random-forest eda naive-bayes-classifier xgboost gbm logistic-regression knn smote

Updated Jan 14, 2021
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Piyush94-BA / Customer-Churn-in-Telecom

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Predicting the churn of customers in a Telecom company using classification algorithms.

telecom imputation smote classification-algorithm business-analytics smote-sampling

Updated May 1, 2020
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shalakasaraogi / credit-card-fraud-detection

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Credit card fraud detection using machine learning techniques

credit-card ros smote fraud-detection random-over-sampling random-under-sampling synthetic-minority-over-sampling

Updated Oct 21, 2020
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atytgat / T-cells-classifier

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Used an ensemble learning approach to distinguish between T-helper and T-regulatory cells, known to be hard to differentiate.

smote genes-data t-cells randomforestclassifier

Updated May 19, 2022
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joviarnandy / Credit-Scoring

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Data Science in the Banking Industry [Volume 1]

machine-learning r classification beginner credit-scoring smote categorical-features heom hvdm

Updated Jul 16, 2020
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Aviator10 / Predicting-Employee-TransportMode

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Predict whether or not an employee will use Car as a mode of transport from given employee information about their mode of transport as well as their personal and professional details like age, salary, work exp. Also, which variables are a significant predictor behind this decision?

machine-learning naive-bayes logistic-regression predictive-modeling knn smote boosting bagging

Updated Apr 16, 2020
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lucashomuniz / Project-6

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Comparing Machine Learning Algorithms for Credit Risk Analysis in Banking

big-data neural-network data-structures data-analysis svm-model bayesian-statistics bank-account smote azure-machine-learning-studio credit-analysis smote-sampling language-r

Updated Jul 11, 2023
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geeky-bit / Census-Data-Imbalanced-Data-Problem

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This is a simple Imbalanced dataset handling problem where I have used Census Data

xgboost imbalanced-data smote

Updated Jan 18, 2018
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Kobamo / Credit-Risk-Analysis

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Credit risk analysis using the LASSO, Random Forests and the SMOTE technique for balancing

classification smote lasso-regression random-forest-classifier credit-risk

Updated Nov 12, 2022
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mnlscn / predicting-modelling-INGBank

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smote meets uplift modeling

r smote uplift-modeling oversa

Updated Jul 25, 2023
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anudeepvanjavakam1 / Income-Classification-of-people-in-US

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a predictive model to determine the income level for people in US. Imputed and manipulated large and high dimensional data using data.table in R. Performed SMOTE as the dataset is highly imbalanced. Developed naïve Bayes, XGBoost and SVM models for classification

machine-learning r high-dimensional-data naive-bayes-classifier classification data-table svm-classifier smote imbalanced-classification xgboost-classifier income-prediction

Updated Nov 22, 2016
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vishakha-b18 / Customer-Churn-in-Telecom

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Predicting the churn of customers in a Telecom company using classification algorithms.

telecom imputation smote classification-algorithm business-analytics smote-sampling

Updated May 5, 2020
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rashmisreenath / Credit-Card-Fraud-Detection

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Credit Card Fraud Detection

smote xgboost-algorithm business-analytics credit-card-fraud-detection

Updated Jul 4, 2022
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EhtashamBillah / Synthetic-Minority-Over-Sampling-Technique-SMOTE-

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For a classification problem, when classes in the dependent variable are severely imbalanced (e.g. 90 yes, 10% no), training an efficient machine learning model becomes very difficult. However with SMOTE method, we can transform the data into a balaced form and train the model efficiently.

machine-learning smote oversampling