https://github.com/abideen-olawuwo/predictive-maintenance
A predictive maintainance model
https://github.com/abideen-olawuwo/predictive-maintenance
decision-trees ipython matplotlib numpy pandas plotly python random-forest seaborn sklearn smote
Last synced: about 1 month ago
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A predictive maintainance model
- Host: GitHub
- URL: https://github.com/abideen-olawuwo/predictive-maintenance
- Owner: abideen-olawuwo
- Created: 2023-05-17T06:02:53.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2023-05-30T13:26:14.000Z (almost 2 years ago)
- Last Synced: 2025-01-19T17:09:52.316Z (3 months ago)
- Topics: decision-trees, ipython, matplotlib, numpy, pandas, plotly, python, random-forest, seaborn, sklearn, smote
- Language: Jupyter Notebook
- Homepage:
- Size: 1.38 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
* Problem Definition
Predicting Machine Failure Type
* Data
The data was downloaded from kaggle[https://www.kaggle.com/datasets/stephanmatzka/predictive-maintenance-dataset-ai4i-2020]
* Evaluation
The Evaluation metric is to get the best accuracy
* Features
The dataset Features include; Product ID, Type, Air temperature, Process temperature, Rotational speed, Torque, Tool wear, Machine failure
TWF, HDF, PWF, OSF, and RNF
* Modelling
The Model used are Random Forest Classifier (RFC), Decision Tree Classifier, GradientBoostingClassifier