from classification import ClassificationModel class LogisticRegression(ClassificationModel): def computeModel(XTrain, yTrain): from sklearn.linear_model import LogisticRegression classifier = LogisticRegression(solver='lbfgs') classifier.fit(XTrain[0], yTrain) return classifier def computeExample(filename): XTrain, XTest, yTrain, yTest = ClassificationModel.preprocessData(filename, True) classifier = LogisticRegression.computeModel(XTrain, yTrain) yPred = ClassificationModel.predictModel(classifier, XTest, False) return ClassificationModel.evaluateModel(yPred, yTest) if __name__ == "__main__": print(LogisticRegression.computeExample("titanic.csv"))