如何获得 0/1 作为二进制预测输出而不是概率?
How to get 0/1 as binary prediction output instead of probabilities?
我训练了一个神经网络模型,得到的预测结果概率在0
和1
之间,如何将它们转换成0/1而不是小数?我设法将它们更改为布尔值:
y_pred
output:
array([[0.05447599],
[0.09883076],
[0.11023161],
...,
[0.19569233],
[0.07266018],
[0.08473385]], dtype=float32)
y_pred_nn = (y_pred_nn > 0.5)
output:
array([[False],
[False],
[False],
...,
[False],
[False],
[False]])
预期结果:
array([[0],
[0],
[0],
...,
[0],
[0],
[0]], dtype=float32)
# just convert to floats then
y_pred_nn = (y_pred_nn > 0.5).astype(np.float32)
我训练了一个神经网络模型,得到的预测结果概率在0
和1
之间,如何将它们转换成0/1而不是小数?我设法将它们更改为布尔值:
y_pred
output:
array([[0.05447599],
[0.09883076],
[0.11023161],
...,
[0.19569233],
[0.07266018],
[0.08473385]], dtype=float32)
y_pred_nn = (y_pred_nn > 0.5)
output:
array([[False],
[False],
[False],
...,
[False],
[False],
[False]])
预期结果:
array([[0],
[0],
[0],
...,
[0],
[0],
[0]], dtype=float32)
# just convert to floats then
y_pred_nn = (y_pred_nn > 0.5).astype(np.float32)