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### Type of Edit (select all that apply)
Add new content (definitions, codeblocks, etc.)
### Description (optional)
Imbalanced dataset is relevant primarily in the context of supervised machine lea…
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Description
Problem Statement:
For a safe and secure lending experience, it's important to analyze the past data. In this project, you have to build a deep learning model to predict the chance of de…
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[This paper](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4189457) is connected to the new minister of communications ([Sattar Hashemi](https://x.com/HashemiSattar)) in Iran: https://x.com/ircf…
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Thanks for maintaining the list of papers on long-tailed learning!
Our work : **SURE: SUrvey REcipes for building reliable and robust deep networks**[CVPR2024] addressed long-tailed distribution in …
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this can be done as activity: giving each team dataset, its description and research question. and ask whether it is ok to use ML:
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## 0. 論文
### タイトル
Max-margin Class Imbalanced Learning with Gaussian Affinity
### リンク
https://arxiv.org/abs/1901.07711
### 著者
Munawar Hayat, Salman Khan, Waqas Zamir, Jianbing Shen, Ling Shao
…
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### Deep Learning for Imbalance Classificaition
#### Survey
1. [A systematic study of the class imbalance problem in convolutional neural networks
Cost-Sensitive](https://arxiv.org/pdf/1710.05381.p…
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Hi! Anyone knows of existing papers or methods, that applies Double ML to highly imbalanced dataset with, for example, a dataset with less than 1% samples being positively treated while the other >99%…
ghost updated
2 years ago
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### Is your proposal related to a problem? Please describe.
I would like to propose a new project to `predict academic risk of students in higher education` using the [dataset provided by the Kaggl…
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# Tweet summary
Train multiple classifiers with bootstrap undersample data set on imbalanced data.
# Useful link
https://www.svds.com/learning-imbalanced-classes/#fn2
https://imbalanced-learn.or…