1

我有一些代码来分析和预测数据集。在我的代码中，预测只有 0 或 1，但在我的 data.csv 中，我有 1 到 7 个输出。在详细模式下，输出可以是 0 或 1。如何解决将输出预测为 3,4 等的问题。

这是我的数据集前 10 行：

1,2,4,4,1,1,3
1,2,4,4,1,2,1
1,2,4,4,1,3,2
1,2,4,4,2,1,3
1,2,4,4,2,2,2
1,2,4,4,2,3,4
1,2,4,4,3,1,3
1,2,4,4,3,2,2
1,2,4,4,3,3,4
1,2,4,5,1,1,3

下面是代码：

from keras.models import Sequential
from keras.layers import Dense
from termcolor import cprint
import numpy


dataset = numpy.loadtxt("C:\\Users\\usr6907\\Desktop\\AIData\\data4.csv", delimiter=",")


X = dataset[:1500,0:6]
Y = dataset[:1500,6]


model = Sequential()
model.add(Dense(30, input_dim=6, init='uniform', activation='relu'))
model.add(Dense(20, init='uniform', activation='relu'))
model.add(Dense(12, init='uniform', activation='relu'))
model.add(Dense(6, init='uniform', activation='relu'))
model.add(Dense(1, init='uniform', activation='sigmoid'))


model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])


model.fit(X, Y, nb_epoch=150, batch_size=10,  verbose=1)


scores = model.evaluate(X, Y)

print("%s: %.2f%%" % (model.metrics_names[1], scores[1]*100))
print("-"*150)


test_verisi = dataset[1500:1728, 0:6]
predictions = model.predict(test_verisi)
dogru = 0
yanlis = 0
toplam_veri = len(dataset[1500:1728,6])

for x, y in zip(predictions, dataset[1500:1728,6]):    
    x = int(numpy.round(x[0]))
    if int(x) == y:
        cprint("Tahmin: "+str(x)+" - Ger�ek De�er: "+str(int(y)), "white", "on_green", attrs=['bold'])
        dogru += 1
    else:
        cprint("Tahmin: "+str(x)+" - Ger�ek De�er: "+str(int(y)), "white", "on_red", attrs=['bold'])
        yanlis += 1

print("\n", "-"*150, "\nISTATISTIK:\nToplam ", toplam_veri, " Veri i�ersinde;\nDo�ru Bilme Say�s�: ", dogru, "\nYanl�� Bilme Say�s�: ",yanlis,
      "\nBa�ar� Y�zdesi: ", str(int(100*dogru/toplam_veri))+"%", sep=' ')
4

0 回答 0