function binaryAccuracy$1(yTrue, yPred) {
	  return binaryAccuracy(yTrue, yPred);
	}
Binary accuracy metric function.

`yTrue` and `yPred` can have 0-1 values. Example:
```js
const x = tf.tensor2d([[1, 1, 1, 1], [0, 0, 0, 0]], [2, 4]);
const y = tf.tensor2d([[1, 0, 1, 0], [0, 0, 0, 1]], [2, 4]);
const accuracy = tf.metrics.binaryAccuracy(x, y);
accuracy.print();
```

`yTrue` and `yPred` can also have floating-number values between 0 and 1, in
which case the values will be thresholded at 0.5 to yield 0-1 values (i.e.,
a value >= 0.5 and <= 1.0 is interpreted as 1.
)
Example:
```js
const x = tf.tensor1d([1, 1, 1, 1, 0, 0, 0, 0]);
const y = tf.tensor1d([0.2, 0.4, 0.6, 0.8, 0.2, 0.3, 0.4, 0.7]);
const accuracy = tf.metrics.binaryAccuracy(x, y);
accuracy.print();
```

@param yTrue Binary Tensor of truth.
@param yPred Binary Tensor of prediction.
@return Accuracy Tensor.

@doc {heading: 'Metrics', namespace: 'metrics'}