Imbalanced 2-class classification project for a predictive modeling competition (13th best ranked team out of a 104)
-
Updated
Feb 6, 2021 - Jupyter Notebook
Imbalanced 2-class classification project for a predictive modeling competition (13th best ranked team out of a 104)
Codebase for "Learn Bayesian Logistic regression from imbalanced data" post.
Experiments with imbalanced data using undersampling and oversampling techniques.
To predict whether a given blight ticket will be paid on time
This project was completed as part of the CIT 650 "Intro To Big Data" course at Nile University.
Analytics Vidhya Hackathon to predict whether the policyholder will file a claim in the next 6 months or not.
This project uses data from Olist - a Brazilian e-commerce platform to predict customer's review scores. The full Python code is presented in 3 steps: data preprocessing, EDA & modeling, followed by a Tableau Dashboard on customer ratings.
Classification models to predict patient length of stay, a multi-class categorical target with imbalanced predictor features. Optimized models include multi-class and voting ensembles.
In this project, I have take bank target marketing dataset with imbalanced classes, I have solved it through GAIN&LIFT chart as well as over-sampling method of sklearn utils.
Credit card detection fraud using fastai.
A python class for making machine learning algorithms cost sensitive.
ML classification on loan data to predict whether loan will default or not.
Research on machine learning, deep learning, and ensemble methods in imbalanced fraud and anomaly detection scenarios.
An Artificial Neural Network (ANN) model detects whether a credit card is fraudulent or not.
New algorithms are designed for imbalanced classification
⚖⚡ Experimental evaluation of ensemble classifiers for imbalance in Big Data.
Harmfulness recognition in Polish language tweets.
웹 광고 클릭률 예측 AI 경진대회, DACON (2024.05.07 ~ 2024.06.03)
A model that will predict whether a customer will leave the bank
Add a description, image, and links to the imbalanced-classification topic page so that developers can more easily learn about it.
To associate your repository with the imbalanced-classification topic, visit your repo's landing page and select "manage topics."