ychervonyi

def auc(labels,
        predictions,
        weights=None,
        num_thresholds=200,
        metrics_collections=None,
        updates_collections=None,
        curve='ROC',
        name=None):
    with variable_scope.variable_scope(name, 'auc',
                                       (labels, predictions, weights)):

ychervonyi

import seaborn as sns
import numpy as np
from sklearn.cross_validation import train_test_split
from sklearn.linear_model import LogisticRegressionCV
from keras.models import Sequential
from keras.layers import Dense, Dropout
from keras.regularizers import l2
from keras.utils import np_utils
import matplotlib.pyplot as plt
import keras

ychervonyi

import seaborn as sns
import numpy as np
from sklearn.model_selection import train_test_split
from keras.models import Sequential
from keras.layers import Dense, Dropout
from keras.regularizers import l2
from keras.utils import np_utils
import matplotlib.pyplot as plt
import keras