Tensorflow.js tf.metrics.precision() Function
Tensorflow.js is an open-source library developed by Google for running machine learning models as well as deep learning neural networks in the browser or node environment.
The .metrics.precision() function is used to calculate the precision of the expectancy with reference to the names.
Syntax:
tf.metrics.precision(yTrue, yPred)
Parameters:
- yTrue: It is the stated ground truth tensor which is supposed to hold values from 0 to 1 and it can be of type tf.Tensor.
- yPred: It is the stated prediction tensor which is supposed to hold values from 0 to 1 and it can be of type tf.Tensor.
Return Value: It returns the tf.Tensor object.
Example 1:
Javascript
import * as tf from "@tensorflow/tfjs"
const y = tf.tensor2d([[0, 1], [1, 1]]);
const z = tf.tensor2d([[1, 0], [0, 1]]);
const pre = tf.metrics.precision(y, z);
pre.print();
|
Output:
Tensor
0.5
Example 2:
Javascript
import * as tf from "@tensorflow/tfjs"
const output = tf.metrics.precision(tf.tensor(
[
[0, 1, 0, 0],
[0, 1, 1, 0],
[0, 0, 0, 1],
[1, 1, 0, 0],
[0, 0, 1, 0]
]
), tf.tensor(
[
[0, 0, 1, 1],
[0, 1, 1, 0],
[0, 0, 0, 1],
[0, 1, 0, 1],
[1, 1, 0, 0]
]
)).print();
|
Output:
Tensor
0.4444444477558136
Reference: https://js.tensorflow.org/api/latest/#metrics.precision
Last Updated :
01 Aug, 2021
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