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--- |
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dataset_info: |
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features: |
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- name: engine_no |
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dtype: int64 |
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- name: time_in_cycles |
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dtype: int64 |
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- name: operational_setting_1 |
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dtype: float64 |
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- name: operational_setting_2 |
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dtype: float64 |
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- name: operational_setting_3 |
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dtype: float64 |
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- name: s_1 |
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dtype: float64 |
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- name: s_2 |
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dtype: float64 |
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- name: s_3 |
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dtype: float64 |
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- name: s_4 |
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dtype: float64 |
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- name: s_5 |
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dtype: float64 |
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- name: s_6 |
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dtype: float64 |
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- name: s_7 |
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dtype: float64 |
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- name: s_8 |
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dtype: float64 |
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- name: s_9 |
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dtype: float64 |
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- name: s_10 |
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dtype: float64 |
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- name: s_11 |
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dtype: float64 |
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- name: s_12 |
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dtype: float64 |
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- name: s_13 |
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dtype: float64 |
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- name: s_14 |
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dtype: float64 |
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- name: s_15 |
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dtype: float64 |
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- name: s_16 |
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dtype: float64 |
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- name: s_17 |
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dtype: float64 |
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- name: s_18 |
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dtype: float64 |
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- name: s_19 |
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dtype: float64 |
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- name: s_20 |
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dtype: float64 |
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- name: s_21 |
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dtype: float64 |
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- name: rul |
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dtype: int64 |
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- name: cluster |
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dtype: int32 |
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- name: condition_ind |
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dtype: float64 |
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splits: |
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- name: train |
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num_bytes: 12257052 |
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num_examples: 53759 |
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- name: test |
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num_bytes: 7749948 |
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num_examples: 33991 |
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download_size: 9762754 |
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dataset_size: 20007000 |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: data/train-* |
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- split: test |
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path: data/test-* |
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--- |
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Feature Engineered version of [this](https://huggingface.co/datasets/uncledecart/fed-turbofan) dataset. Key differences: |
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- GBDT feature selection (selected on train data, target is rul, threshold is 0.01, lightgbm.LGBMRegressor is used) |
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- Sensor-wise z_score and min_max normalisation (effectively just min_max, applied z_score as in [this](https://www.researchgate.net/publication/355164116_Data-Driven_Deep_Learning-Based_Attention_Mechanism_for_Remaining_Useful_Life_Prediction_Case_Study_Application_to_Turbofan_Engine_Analysis) paper) |
