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tft.bucketize

Returns a bucketized column, with a bucket index assigned to each input.

Used in the notebooks

Used in the tutorials

`x` A numeric input `Tensor` or `CompositeTensor` whose values should be mapped to buckets. For a `CompositeTensor` only non-missing values will be included in the quantiles computation, and the result of `bucketize` will be a `CompositeTensor` with non-missing values mapped to buckets. If elementwise=True then `x` must be dense.
`num_buckets` Values in the input `x` are divided into approximately equal-sized buckets, where the number of buckets is `num_buckets`.
`epsilon` (Optional) Error tolerance, typically a small fraction close to zero. If a value is not specified by the caller, a suitable value is computed based on experimental results. For `num_buckets` less than 100, the value of 0.01 is chosen to handle a dataset of up to ~1 trillion input data values. If `num_buckets` is larger, then epsilon is set to (1/`num_buckets`) to enforce a stricter error tolerance, because more buckets will result in smaller range for each bucket, and so we want the boundaries to be less fuzzy. See analyzers.quantiles() for details.
`weights` (Optional) Weights tensor for the quantiles. Tensor must have the same shape as x.
`elementwise` (Optional) If true, bucketize each element of the tensor independently.
`name` (Optional) A name for this operation.

A `Tensor` of the same shape as `x`, with each element in the returned tensor representing the bucketized value. Bucketized value is in the range [0, actual_num_buckets). Sometimes the actual number of buckets can be different than num_buckets hint, for example in case the number of distinct values is smaller than num_buckets, or in cases where the input values are not uniformly distributed. NaN values are mapped to the last bucket. Values with NaN weights are ignored in bucket boundaries calculation.

`TypeError` If num_buckets is not an int.
`ValueError` If value of num_buckets is not > 1.
`ValueError` If elementwise=True and x is a `CompositeTensor`.

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[{ "type": "thumb-up", "id": "easyToUnderstand", "label":"Easy to understand" },{ "type": "thumb-up", "id": "solvedMyProblem", "label":"Solved my problem" },{ "type": "thumb-up", "id": "otherUp", "label":"Other" }]