从Keras模型获取混淆矩阵 [英] Get confusion matrix from a Keras model

问题描述

我有以下使用Keras的NN模型:

I have the following NN model using Keras:

import numpy as np
from keras import Sequential
from keras.layers import Dense

path = 'pima-indians-diabetes.data.csv'
dataset = np.loadtxt(path, delimiter=",")
X = dataset[:,0:8]
Y = dataset[:,8]
X_train, X_test, y_train, y_test = train_test_split(X, Y, test_size=0.2)

model = Sequential()
model.add(Dense(16, input_dim=8, activation='relu'))
model.add(Dense(32, activation='relu'))
model.add(Dense(1, activation='sigmoid'))

model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])
model.fit(X_train, y_train, epochs=100, batch_size=16, validation_data=(X_test, y_test))

请问是否可以提取confusion matrix?怎么样?

Kindly, is it possible to extract the confusion matrix? How?

推荐答案

您可以使用 scikit学习:

y_pred = model.predict(X_test)
confusion_matrix = sklearn.metrics.confusion_matrix(y_test, np.rint(y_pred))

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