•1 min read•from Machine Learning
[P] Extreme Imbalance Data from 100K dataset only have 56 failure [P]
![[P] Extreme Imbalance Data from 100K dataset only have 56 failure [P]](/_next/image?url=https%3A%2F%2Fpreview.redd.it%2Fplbydmenmm6h1.png%3Fwidth%3D140%26height%3D23%26auto%3Dwebp%26s%3D5ea145541663231254f92fd815bb1237861fd6cb&w=3840&q=75)
![[P] Extreme Imbalance Data from 100K dataset only have 56 failure [P]](https://preview.redd.it/plbydmenmm6h1.png?width=140&height=23&auto=webp&s=5ea145541663231254f92fd815bb1237861fd6cb "[P] Extreme Imbalance Data from 100K dataset only have 56 failure [P]") | as in the title, my goal is to predicting failure and RUL of machine, dataset is timestamp and when machine is failure it will labeled with 1 that only have 56 From this data im ditching operating hours and humidity because it didnt show correlation for machine failure, what algorithm or deeplearning suit for it? [link] [comments] |
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