There are 3 repositories under unbalanced-data topic.
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.
🎵 Using Deep Learning to Categorize Music as Time Progresses Through Spectrogram Analysis
Adversarial Attack on 3D U-Net model: Brain Tumour Segmentation.
Implementation of Random Balance Algorithm
Customer churn analysis for a telecommunication company
Classification on Unbalanced Datasets using Boost Techniques (AdaBoost M2, SMOTE Boost, RusBoost,..)
This repo contains work carried out for SemEval 2022 Task 6: iSarcasmEval: Intended Sarcasm Detection In English and Arabic
Fault diagnosis using focus loss function based on balance factor (two-category)
predicting whether you read mail
Multinomial classification tasks in Reddit
Identify fraudulent credit card transactions so that customers are not charged for items that they did not purchase. (Python, Logistic Regression Classifier, Unbalanced dataset).
Web Scrapping British Airways review to gain company insights. Build a random forest model to predict customer buying behavior.
Predict if a transaction is a fraud transaction or not, also, dealing with unbalanced data and finding the pattern using correlation between the features.
Deep learning solution for Cassava Leaf Disease Classification, a Kaggle's Research Code Competition using Tensorflow.
predicting showing up to doctor's appointment using mlp on imbalance dataset.
Code for dealing with undersampling and oversampling which are standard strategies for dealing with unbalanced class data
Classfying an unbalanced data set of delayed flights with the help of SMOTE and comparing the performance of three different classification models (Decision Tree, Logistic Regression, XGBoost).
It's a classification model that predict whether an individual will suffer from autism in future or not
Insurance reports through deep neural networks
To solve two main issues in credit card fraud detection - skewness of the data and cost-sensitivity
Parkinson diagnostic with supervised and unsupervised machine learning
Train JOSA (Jopara Sentiment Analysis) corpus with traditional machine learning algorithms.
A submission for HUAWEI - 2020 DIGIX GLOBAL AI CHALLENGE
Unbalanced Customer Data
Classify default borrowers from initial loan application for Lending Club
To predict whether the customers will subscribe to the system after 1-month free trial or not.
Applying CRISP-DM methodology for predicting Loan Elegibility
research on unbalanced data problems
Credit card fraud detection with CNN genetic algorithm and SVM
classification of online purchasing rates
(Python) Proyecto enfocado en la creación de modelos predictivos como Regresión Logistica, Arboles de Decisión, KNN, SVM, Naive Bayes y Ensamblados. Inicialmente el problema consta de un analisis crediticio de clientes buenos/malos. Se utiliza una BBDD de clases desbalanceadas la cual se limpia y procesa para alimentar los modelos
Predicting Machine failure using Machine learning on a synthetic dataset of an existing milling machine consisting of 10,000 data points