tf.contrib.learn.BaseEstimator.predict(*args, **kwargs)
Returns predictions for given features. (deprecated arguments)
SOME ARGUMENTS ARE DEPRECATED. They will be removed after 2016-09-15. Instructions for updating: The default behavior of predict() is changing. The default value for as_iterable will change to True, and then the flag will be removed altogether. The behavior of this flag is described below.
Args: x: Matrix of shape [n_samples, n_features...]. Can be iterator that returns arrays of features. The training input samples for fitting the model. If set, `input_fn` must be `None`. input_fn: Input function. If set, `x` and 'batch_size' must be `None`. batch_size: Override default batch size. If set, 'input_fn' must be 'None'. outputs: list of `str`, name of the output to predict. If `None`, returns all. as_iterable: If True, return an iterable which keeps yielding predictions for each example until inputs are exhausted. Note: The inputs must terminate if you want the iterable to terminate (e.g. be sure to pass num_epochs=1 if you are using something like read_batch_features). Returns: A numpy array of predicted classes or regression values if the constructor's `model_fn` returns a `Tensor` for `predictions` or a `dict` of numpy arrays if `model_fn` returns a `dict`. Returns an iterable of predictions if as_iterable is True. Raises: ValueError: If x and input_fn are both provided or both `None`.
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