from sklearn.linear_model import LogisticRegression as Model
def train(features, target):
    model = Model()
    model.fit(features, target)
    return model

def predict(model, new_features):
    preds = model.predict(new_features)
    return preds

feats = [[5, 2, 0], [10, 2, 0], [10, 10, 0], [5, 2, 0], [2, 10, 0], [10, 9, 0], [10, 2, 1], [5, 2, 246], [10, 9, 232]]
target = [1, 0, 1, 0, 1, 0, 1, 1, 1]
model = train(feats, target)
test = [[10000, 1000, 0]]
predictions = predict(model, test)
print(predictions)