Guangning Yu's Blog

#!/usr/bin/env python
import urllib2
import numpy as np
from keras.models import Sequential
from keras.layers import Dense
from keras.wrappers.scikit_learn import KerasRegressor
from sklearn.model_selection import cross_val_score
from sklearn.model_selection import KFold
from sklearn.preprocessing import StandardScaler
from sklearn.pipeline import Pipeline
def load_data():
    X = []
    Y = []
    data_url = 'https://archive.ics.uci.edu/ml/machine-learning-databases/housing/housing.data'
    for line in urllib2.urlopen(data_url).readlines():
        line = map(float, line.split())
        X.append(line[0:13])
        Y.append(line[13])
    return X, Y
def basic_model():
    # create model
    model = Sequential()
    model.add(Dense(13, input_dim=13, kernel_initializer='normal', activation='relu'))
    model.add(Dense(1, kernel_initializer='normal'))
    # compile model
    model.compile(loss='mean_squared_error', optimizer='adam')
    return model
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