Translations:Dimensionner et faire un tracker solaire photovolatïque low tech/275/en

class ML():

   @staticmethod
   def ml(X,y,classifier):
       "process machine learning on X data set, y yes/no data with classifier"
       # dataset
       #X = images_video
       #y = positives
       # classifier model training
       clf = ML.dico_classifier[classifier]()
       X_train, X_test, y_train, y_test = sklearn.model_selection.train_test_split(
           X, y, random_state=0)
       clf.fit(X_train, y_train)
       # predictions
       _predicted = clf.predict(X_test)
       # scores
       _accuracy, _precision, _recall = ML.compute_scores(y_test, _predicted,
                                                       classifier)
       # confusion matrix
       ML.compute_confusion_matrix(y_test, _predicted, _accuracy, classifier)
       # courbes precision-recall
       ML.plot_precision_recall(clf, X_test, y_test, classifier, _predicted)
       # roc
       roc_auc_clf = ML.plot_roc(clf, X_test, y_test, classifier)[0]
       return pd.DataFrame(data=(_accuracy, _precision, _recall, roc_auc_clf),
                           index=['accuracy', 'precision', 'recall', 'AUC'],
                           columns=[classifier])