我需要将我的字符串标签转换为像 [0, 0, ... , 1, ... 0] 这样的向量。
据我所知,这是一种称为一个热向量的东西。
我有 10 个类,所以有 10 个不同的字符串标签。
任何人都可以帮助进行直接和逆变换吗?
我是 tensorflow 的新手,所以请善待。
最佳答案
向前的方向很容易,因为有 tf.one_hot
操作:
import tensorflow as tf
original_indices = tf.constant([1, 5, 3])
depth = tf.constant(10)
one_hot_encoded = tf.one_hot(indices=original_indices, depth=depth)
with tf.Session():
print(one_hot_encoded.eval())
输出:
[[ 0. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
[ 0. 0. 0. 0. 0. 1. 0. 0. 0. 0.]
[ 0. 0. 0. 1. 0. 0. 0. 0. 0. 0.]]
反过来也不错,
tf.where
找到非零索引:def decode_one_hot(batch_of_vectors):
"""Computes indices for the non-zero entries in batched one-hot vectors.
Args:
batch_of_vectors: A Tensor with length-N vectors, having shape [..., N].
Returns:
An integer Tensor with shape [...] indicating the index of the non-zero
value in each vector.
"""
nonzero_indices = tf.where(tf.not_equal(
batch_of_vectors, tf.zeros_like(batch_of_vectors)))
reshaped_nonzero_indices = tf.reshape(
nonzero_indices[:, -1], tf.shape(batch_of_vectors)[:-1])
return reshaped_nonzero_indices
with tf.Session():
print(decode_one_hot(one_hot_encoded).eval())
打印:
[1 5 3]
关于tensorflow - 如何在 TensorFlow 中编码标签?,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/42092508/