Python LogisticRegression примеры использования

Пример #1

Файл: ner_baseline.py Проект: Sebster10/Pandas-Practice

def main():
    Xtrain, Ytrain, Xtest, Ytest, word2idx, tag2idx = get_data()

    V = len(word2idx)
    print("vocabulary size:", V)
    K = len(tag2idx)

    # train and score
    model = LogisticRegression()
    model.fit(Xtrain, Ytrain, V=V, K=K, epochs=5)
    print("training complete")
    print("train score:", model.score(Xtrain, Ytrain))
    print("train f1 score:", model.f1_score(Xtrain, Ytrain))
    print("test score:", model.score(Xtest, Ytest))
    print("test f1 score:", model.f1_score(Xtest, Ytest))

Пример #2

Файл: ner_baseline.py Проект: renjinghai/machine_learning_examples

def main():
    Xtrain, Ytrain, Xtest, Ytest, word2idx, tag2idx = get_data()

    V = len(word2idx)
    print "vocabulary size:", V
    K = len(tag2idx)

    # train and score
    model = LogisticRegression()
    model.fit(Xtrain, Ytrain, V=V, K=K, epochs=5)
    print "training complete"
    print "train score:", model.score(Xtrain, Ytrain)
    print "train f1 score:", model.f1_score(Xtrain, Ytrain)
    print "test score:", model.score(Xtest, Ytest)
    print "test f1 score:", model.f1_score(Xtest, Ytest)

Пример #3

Файл: ner_baseline.py Проект: OscarAbacka/machine_learning_examples

#     return Xtrain, Ytrain, Xtest, Ytest, word2idx, tag2idx


def main():
    Xtrain, Ytrain, Xtest, Ytest, word2idx, tag2idx = get_data()

    V = len(word2idx)
<<<<<<< HEAD
    print "vocabulary size:", V
=======
    print("vocabulary size:", V)
>>>>>>> upstream/master
    K = len(tag2idx)

    # train and score
    model = LogisticRegression()
    model.fit(Xtrain, Ytrain, V=V, K=K, epochs=5)
<<<<<<< HEAD
    print "training complete"
    print "train score:", model.score(Xtrain, Ytrain)
    print "train f1 score:", model.f1_score(Xtrain, Ytrain)
    print "test score:", model.score(Xtest, Ytest)
    print "test f1 score:", model.f1_score(Xtest, Ytest)
=======
    print("training complete")
    print("train score:", model.score(Xtrain, Ytrain))
    print("train f1 score:", model.f1_score(Xtrain, Ytrain))
    print("test score:", model.score(Xtest, Ytest))
    print("test f1 score:", model.f1_score(Xtest, Ytest))
>>>>>>> upstream/master