tf.contrib.learn.TensorFlowEstimator.get_variable_value()
  • References/Big Data/TensorFlow/TensorFlow Python/Learn

tf.contrib.learn.TensorFlowEstimator.get_variable_value(name) Returns value of the variable given by name.

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tf.contrib.learn.Estimator.get_variable_value()
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tf.contrib.learn.Estimator.get_variable_value(name) Returns value of the variable given by name. Args:

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tf.contrib.learn.Estimator.evaluate()
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tf.contrib.learn.Estimator.evaluate(x=None, y=None, input_fn=None, feed_fn=None, batch_size=None, steps=None, metrics=None, name=None) See

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tf.contrib.learn.ModeKeys
  • References/Big Data/TensorFlow/TensorFlow Python/Learn

class tf.contrib.learn.ModeKeys Standard names for model modes. The following standard keys are

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tf.contrib.learn.LinearClassifier.get_variable_value()
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tf.contrib.learn.LinearClassifier.get_variable_value(name)

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tf.contrib.learn.DNNClassifier.predict()
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tf.contrib.learn.DNNClassifier.predict(*args, **kwargs) Returns predicted classes for given features. (deprecated arguments)

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tf.contrib.learn.TensorFlowRNNRegressor.partial_fit()
  • References/Big Data/TensorFlow/TensorFlow Python/Learn

tf.contrib.learn.TensorFlowRNNRegressor.partial_fit(x, y) Incremental fit on a batch of samples. This

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tf.contrib.learn.Estimator.
  • References/Big Data/TensorFlow/TensorFlow Python/Learn

tf.contrib.learn.Estimator.__init__(model_fn=None, model_dir=None, config=None, params=None, feature_engineering_fn=None) Constructs

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tf.contrib.learn.LinearClassifier.get_variable_names()
  • References/Big Data/TensorFlow/TensorFlow Python/Learn

tf.contrib.learn.LinearClassifier.get_variable_names()

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tf.contrib.learn.BaseEstimator.fit()
  • References/Big Data/TensorFlow/TensorFlow Python/Learn

tf.contrib.learn.BaseEstimator.fit(x=None, y=None, input_fn=None, steps=None, batch_size=None, monitors=None, max_steps=None) See

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