F1-score metric for TensorFlow
Project description
tf1
F1-score metrics for classification models in TensorFlow. There are 3 average modes provided:
- binary
- macro
- micro
Usage
from tf1 import f1_binary
# use f1_binary as any other metric from tf.metrics.*
Note, that due to streaming nature of metric computation process, "macro" and "micro" average metrics should know total number of classes. Use them as follows:
from tf1 import f1_macro, f1_micro
def my_task_f1_macro(
labels, predictions, num_classes, weights=None,
metrics_collections=None, updates_collections=None,
name=None):
return f1_macro(
labels=labels,
predictions=predictions,
num_classes=123, # Required
weights=weights,
metrics_collections=metrics_collections,
updates_collections=updates_collections,
name=name
)
# use my_task_f1_macro as any other metric from tf.metrics.*
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