35 lines
791 B
Python
35 lines
791 B
Python
|
import numpy as np
|
||
|
|
|
||
|
|
def get_entropy(probs):
|
||
|
|
return np.sum( np.multiply(probs, np.log(probs + 1e-20)) , axis=1)
|
||
|
|
|
||
|
|
def get_max_conf(probs):
|
||
|
|
return np.max(probs, axis=-1)
|
||
|
|
|
||
|
|
def find_ATC_threshold(scores, labels):
|
||
|
|
sorted_idx = np.argsort(scores)
|
||
|
|
|
||
|
|
sorted_scores = scores[sorted_idx]
|
||
|
|
sorted_labels = labels[sorted_idx]
|
||
|
|
|
||
|
|
fp = np.sum(labels==0)
|
||
|
|
fn = 0.0
|
||
|
|
|
||
|
|
min_fp_fn = np.abs(fp - fn)
|
||
|
|
thres = 0.0
|
||
|
|
for i in range(len(labels)):
|
||
|
|
if sorted_labels[i] == 0:
|
||
|
|
fp -= 1
|
||
|
|
else:
|
||
|
|
fn += 1
|
||
|
|
|
||
|
|
if np.abs(fp - fn) < min_fp_fn:
|
||
|
|
min_fp_fn = np.abs(fp - fn)
|
||
|
|
thres = sorted_scores[i]
|
||
|
|
|
||
|
|
return min_fp_fn, thres
|
||
|
|
|
||
|
|
|
||
|
|
def get_ATC_acc(thres, scores):
|
||
|
|
return np.mean(scores>=thres)*100.0
|