A user on r/MachineLearning is seeking advice on predicting machine failures using a dataset with extreme class imbalance. The dataset contains 100,000 entries, but only 56 instances are labeled as failures. The user has found that operating hours and humidity do not correlate with failures and is looking for suitable algorithms or deep learning approaches to handle this data scarcity for failure prediction and remaining useful life (RUL) estimation. AI
RANK_REASON This is a user query on a forum, not a research paper, model release, or industry news.
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