This is the corresponding repository of paper Limited Data Rolling Bearing Fault Diagnosis with Few-shot Learning

Cost-Sensitive Learning / ReSampling / Weighting / Thresholding / BorderlineSMOTE / AdaCost / etc.

[Likelihood Lab Project 2024] Official Repository for The Technical Report, Label Unbalance in High-frequency Trading

🎵 Using Deep Learning to Categorize Music as Time Progresses Through Spectrogram Analysis

Adversarial Attack on 3D U-Net model: Brain Tumour Segmentation.

Classification on Unbalanced Datasets using Boost Techniques (AdaBoost M2, SMOTE Boost, RusBoost,..)

Implementation of Random Balance Algorithm

This repo contains work carried out for SemEval 2022 Task 6: iSarcasmEval: Intended Sarcasm Detection In English and Arabic

Customer churn analysis for a telecommunication company

No description provided.

predicting whether you read mail

Web Scrapping British Airways review to gain company insights. Build a random forest model to predict customer buying behavior.

Identify fraudulent credit card transactions so that customers are not charged for items that they did not purchase. (Python, Logistic Regression Classifier, Unbalanced dataset).

predicting showing up to doctor's appointment using mlp on imbalance dataset.

To solve two main issues in credit card fraud detection - skewness of the data and cost-sensitivity

Multinomial classification tasks in Reddit

Toy-project, unbalanced data, classification pipeline for multiple classifiers and parameters tuning.

research on unbalanced data problems

Train JOSA (Jopara Sentiment Analysis) corpus with traditional machine learning algorithms.

Applying CRISP-DM methodology for predicting Loan Elegibility

Fault diagnosis using focus loss function based on balance factor (two-category)

This project aims to solve a classic Machine Learning problem involving neural networks, tree classification, regressions, and clustering.

No description provided.

It's a classification model that predict whether an individual will suffer from autism in future or not

Parkinson diagnostic with supervised and unsupervised machine learning

Classify default borrowers from initial loan application for Lending Club

Code for dealing with undersampling and oversampling which are standard strategies for dealing with unbalanced class data

Insurance reports through deep neural networks

To predict whether the customers will subscribe to the system after 1-month free trial or not.

Unbalanced Customer Data