This is the corresponding repository of paper Limited Data Rolling Bearing Fault Diagnosis with Few-shot Learning
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Updated
Oct 10, 2022 - Jupyter Notebook
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
Implementation of Random Balance Algorithm
Classification on Unbalanced Datasets using Boost Techniques (AdaBoost M2, SMOTE Boost, RusBoost,..)
Customer churn analysis for a telecommunication company
predicting whether you read mail
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.
To solve two main issues in credit card fraud detection - skewness of the data and cost-sensitivity
Multinomial classification tasks in Reddit
Classify default borrowers from initial loan application for Lending Club
research on unbalanced data problems
Fault diagnosis using focus loss function based on balance factor (two-category)
It's a classification model that predict whether an individual will suffer from autism in future or not
Train JOSA (Jopara Sentiment Analysis) corpus with traditional machine learning algorithms.
Applying CRISP-DM methodology for predicting Loan Elegibility
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