import pandas as pd
import numpy as np
import keras
from keras.models import Sequential
from keras.layers import Dense, Dropout

previsores = pd.read_csv('entradas-breast.csv')
classe = pd.read_csv('saidas-breast.csv')

classificador = Sequential()
classificador.add(Dense(units = 8, activation = 'relu', kernel_initializer = 'normal', input_dim = 30))
classificador.add(Dropout(0.2))
classificador.add(Dense(units = 8, activation = 'relu', kernel_initializer = 'normal'))
classificador.add(Dropout(0.2))
classificador.add(Dense(units = 1, activation = 'sigmoid'))
classificador.compile(optimizer = 'adam', loss = 'binary_crossentropy' ,metrics = ['binary_accuracy'])
classificador.fit(previsores,classe, batch_size = 10, epochs = 100)

novo = np.array([[15.80,8.34,118,900,0.1,0.26,0.08,0.134,0.178,0.2,0.05,1098,0.87,4500,145.2,0.005,0.04,0.05,0.015,0.03,0.007,23.15,16.64,178.5,2018,0.14,0.184,0.84,158,0.363]])

previsao = classificador.predict(novo)