I have implemented a Nueral Network model for a classification with the help of using TensorFlow. But, i don't know how can i able to draw confusion matrix by using predicted scores (accuracy). I am not an expert of TensorFlow and still in learning phase. Here i pasted my code below please tell me how can i write a code for making confusion from the following code:
# Launch the graph
with tf.Session() as sess:
sess.run(init)
# Set logs writer into folder /tmp/tensorflow_logs
#summary_writer = tf.train.SummaryWriter('/tmp/tensorflow_logs', graph_def=sess.graph_def)
# Training cycle
for epoch in range(training_epochs):
avg_cost = 0.
total_batch = int(X_train.shape[0]/batch_size)
# Loop over total length of batches
for i in range(total_batch):
#picking up random batches from training set of specific size
batch_xs, batch_ys = w2v_utils.nextBatch(X_train, y_train, batch_size)
# Fit training using batch data
sess.run(optimizer, feed_dict={x: batch_xs, y: batch_ys})
# Compute average loss
avg_cost += sess.run(cost, feed_dict={x: batch_xs, y: batch_ys})/total_batch
# Write logs at every iteration
#summary_str = sess.run(merged_summary_op, feed_dict={x: batch_xs, y: batch_ys})
#summary_writer.add_summary(summary_str, epoch*total_batch + i)
#append loss
loss_history.append(avg_cost)
# Display logs per epoch step
if (epoch % display_step == 0):
correct_prediction = tf.equal(tf.argmax(pred, 1), tf.argmax(y, 1))
# Calculate training accuracy
accuracy = tf.reduce_mean(tf.cast(correct_prediction, "float"))
trainAccuracy = accuracy.eval({x: X_train, y: y_train})
train_acc_history.append(trainAccuracy)
# Calculate validation accuracy
valAccuracy = accuracy.eval({x: X_val, y: y_val})
val_acc_history.append(valAccuracy)
print "Epoch:", '%04d' % (epoch+1), "cost=", "{:.9f}".format(avg_cost), "train=",trainAccuracy,"val=", valAccuracy
print "Optimization Finished!"
# Test model
correct_prediction = tf.equal(tf.argmax(pred, 1), tf.argmax(y, 1))
# Calculate accuracy
accuracy = tf.reduce_mean(tf.cast(correct_prediction, "float"))
print "Final Training Accuracy:", accuracy.eval({x: X_train, y: y_train})
print "Final Test Accuracy:", accuracy.eval({x: X_test, y: y_test})
print "Final Gold Accuracy:", accuracy.eval({x: X_gold, y: y_gold})
Up till now, i am able to print predicted scores but failed to implement confusion matrix please help.
Note:(I am using one hot vectors for representing my labels)
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