spicyramen

# Create your first MLP in Keras
from keras.models import Sequential
from keras.layers import Dense
import numpy

FILENAME = '../data/pima-indians-diabetes.csv'

# Fix random seed for reproducibility.
seed = 7
numpy.random.seed(seed)

spicyramen

# MLP with manual validation set
from keras.models import Sequential
from keras.layers import Dense
from sklearn.model_selection import train_test_split
import numpy as np

# fix random seed for reproducibility
seed = 7
np.random.seed(seed)
# load pima indians dataset

spicyramen

# MLP with manual validation set
from keras.models import Sequential
from keras.layers import Dense
from sklearn.model_selection import train_test_split
import numpy as np

# fix random seed for reproducibility
seed = 7
np.random.seed(seed)
# load pima indians dataset

spicyramen

# MLP for Pima Indians Dataset with 10-fold cross validation
from keras.models import Sequential
from keras.layers import Dense
from sklearn.model_selection import StratifiedKFold
import numpy

# fix random seed for reproducibility
seed = 7
numpy.random.seed(seed)
# load pima indians dataset