tf.keras.layers.experimental.preprocessing.Discretization

Buckets data into discrete ranges.

Inherits From: Layer

Used in the notebooks

Used in the tutorials

This layer will place each element of its input data into one of several contiguous ranges and output an integer index indicating which range each element was placed in.

Input shape:

Any tf.Tensor or tf.RaggedTensor of dimension 2 or higher.

Output shape:

Same as input shape.

Examples:

Bucketize float values based on provided buckets.

input = np.array([[-1.5, 1.0, 3.4, .5], [0.0, 3.0, 1.3, 0.0]]) layer = tf.keras.layers.experimental.preprocessing.Discretization( ... bins=[0., 1., 2.]) layer(input)

bins Optional boundary specification. Bins include the left boundary and exclude the right boundary, so bins=[0., 1., 2.] generates bins (-inf, 0.), [0., 1.), [1., 2.), and [2., +inf).