ReneWind operates wind farms. Unexpected turbine failures are presenting operational and financial problems. This project uses machine learning to develop a model that accurately predict component failure, which will give the firm more control over maintenance scheduling, costs and power generation.
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ReneWind operates wind farms. Unexpected turbine failures are presenting operational and financial problems. This project uses machine learning to develop a model that accurately predict component failure, which will give the firm more control over maintenance scheduling, costs and power generation.
tpurcell0122github/ReneWind
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ReneWind operates wind farms. Unexpected turbine failures are presenting operational and financial problems. This project uses machine learning to develop a model that accurately predict component failure, which will give the firm more control over maintenance scheduling, costs and power generation.
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validation
cross-validation
pipelines
logistic-regression
confusion-matrix
tuning-parameters
hyperparameter-tuning
decision-tree-classifier
oversampling
bagging
undersampling
random-forest-classifier
xgboost-classifier
heatmap-visualization
xgbclassifier
adaboostclassifier
featureimportances
missingvalues
gradientboostingclassifier
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