unbalanced-data
There are 76 repositories under unbalanced-data topic.
SNBQT/Limited-Data-Rolling-Bearing-Fault-Diagnosis-with-Few-shot-Learning
This is the corresponding repository of paper Limited Data Rolling Bearing Fault Diagnosis with Few-shot Learning
Albertsr/Class-Imbalance
Cost-Sensitive Learning / ReSampling / Weighting / Thresholding / BorderlineSMOTE / AdaCost / etc.
evanotero/deep-music-genre-classification
🎵 Using Deep Learning to Categorize Music as Time Progresses Through Spectrogram Analysis
tarun360/Adversarial-Attack-on-3D-U-Net-model-Brain-Tumour-Segmentation.
Adversarial Attack on 3D U-Net model: Brain Tumour Segmentation.
soroushjavdan/RandomBalanceBoost
Implementation of Random Balance Algorithm
SaeidRostami/Customer_Churn
Customer churn analysis for a telecommunication company
celestialtaha/Unbalanced-dataset-Classification
Classification on Unbalanced Datasets using Boost Techniques (AdaBoost M2, SMOTE Boost, RusBoost,..)
rematchka/Intended-Sarcasm-Detection-In-English-and-Arabic-for-extremly-unbalanced-datasets
This repo contains work carried out for SemEval 2022 Task 6: iSarcasmEval: Intended Sarcasm Detection In English and Arabic
wyuechuan/Focal-loss-and-balance-factor-for-classification
Fault diagnosis using focus loss function based on balance factor (two-category)
Go-MinSeong/Predicting-whether-your-mail-will-be-read
predicting whether you read mail
jCodingStuff/NLPReddit
Multinomial classification tasks in Reddit
kpratikin/Credit-Card-Fraud
Identify fraudulent credit card transactions so that customers are not charged for items that they did not purchase. (Python, Logistic Regression Classifier, Unbalanced dataset).
aabritidutta/Creditcard-Fraud-Detection
Predict if a transaction is a fraud transaction or not, also, dealing with unbalanced data and finding the pattern using correlation between the features.
AkashSDas/cassava-leaf-disease-classification
Deep learning solution for Cassava Leaf Disease Classification, a Kaggle's Research Code Competition using Tensorflow.
Bushramjad/Image-classification-with-unbalanced-classes
Code for dealing with undersampling and oversampling which are standard strategies for dealing with unbalanced class data
dadavalangege/Classification_Models
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).
GayatriSharma23/Autism-Prediction
It's a classification model that predict whether an individual will suffer from autism in future or not
isaaccs/Insurance-reports-through-deep-neural-networks
Insurance reports through deep neural networks
JoyWang0320/Data-Mining_Credit-Card-Fraud-Detection
To solve two main issues in credit card fraud detection - skewness of the data and cost-sensitivity
MaryemSamet/Parkinson-diagnostic
Parkinson diagnostic with supervised and unsupervised machine learning
mmaguero/textcat-josa
Train JOSA (Jopara Sentiment Analysis) corpus with traditional machine learning algorithms.
mustafahakkoz/Advertisement-CTR-Prediction
A submission for HUAWEI - 2020 DIGIX GLOBAL AI CHALLENGE
newsteps8/Term-Deposit-Prediction
Unbalanced Customer Data
RickFSA/Lending_Club_Default_Prediction
Classify default borrowers from initial loan application for Lending Club
SimarjotKaur/Customer-Churn-Prediction
To predict whether the customers will subscribe to the system after 1-month free trial or not.
ValeriaPineda23/Loan-Eligibility-Predictions
Applying CRISP-DM methodology for predicting Loan Elegibility
yuneming/UnbalancedDataLearning
research on unbalanced data problems
ahmadara/Credit-card-fraud-detection
Credit card fraud detection with CNN genetic algorithm and SVM
jaymax01/predicting-customer-purchases
classification of online purchasing rates
taisakamisarava/Employee-Salary-prediction
The model aimed at prediction of employee's salary
thomasfsr/unbalanced_data_classifier
⚖Unbalanced data of diabetes classification
Leoelsilva/predictiveanalytics
(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
Safaa-p/Machine-Failure-Prediction
Predicting Machine failure using Machine learning on a synthetic dataset of an existing milling machine consisting of 10,000 data points