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"))
