python - How to calculate precision and recall in Keras

Question

I am building a multi-class classifier with Keras 2.02 (with Tensorflow backend)，and I do not know how to calculate precision and recall in Keras. Please help me.

Answer 1

Python package keras-metrics could be useful for this (I'm the package's author).

import keras
import keras_metrics

model = models.Sequential()
model.add(keras.layers.Dense(1, activation="sigmoid", input_dim=2))
model.add(keras.layers.Dense(1, activation="softmax"))

model.compile(optimizer="sgd",
              loss="binary_crossentropy",
              metrics=[keras_metrics.precision(), keras_metrics.recall()])

UPDATE: Starting with Keras version 2.3.0, such metrics as precision, recall, etc. are provided within library distribution package.

The usage is the following:

model.compile(optimizer="sgd",
              loss="binary_crossentropy",
              metrics=[keras.metrics.Precision(), keras.metrics.Recall()])