Training sklearn models in parallel with joblib blocks the process
问题 As suggested in this answer, I tried to use joblib to train multiple scikit-learn models in parallel. import joblib import numpy from sklearn import tree, linear_model classifierParams = { "Decision Tree": (tree.DecisionTreeClassifier, {}),'' "Logistic Regression" : (linear_model.LogisticRegression, {}) } XTrain = numpy.array([[1,2,3],[4,5,6]]) yTrain = numpy.array([0, 1]) def trainModel(name, clazz, params, XTrain, yTrain): print("training ", name) model = clazz(**params) model.fit(XTrain,