tf.contrib.learn.TensorFlowEstimator.

tf.contrib.learn.TensorFlowEstimator.__repr__()

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tf.contrib.learn.TensorFlowRNNRegressor.partial_fit()

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

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tf.contrib.learn.TensorFlowRNNRegressor.config

tf.contrib.learn.TensorFlowRNNRegressor.config

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tf.contrib.learn.TensorFlowRNNClassifier.predict_proba()

tf.contrib.learn.TensorFlowRNNClassifier.predict_proba(x, batch_size=None) Predict class probability of the input samples x

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tf.contrib.learn.TensorFlowRNNRegressor.evaluate()

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

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tf.contrib.learn.Estimator.get_variable_value()

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

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tf.contrib.learn.BaseEstimator.fit()

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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tf.contrib.learn.TensorFlowEstimator.fit()

tf.contrib.learn.TensorFlowEstimator.fit(x, y, steps=None, monitors=None, logdir=None) Neural network model from provided model_fn

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tf.contrib.learn.LinearClassifier.get_variable_value()

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

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tf.contrib.learn.TensorFlowEstimator.get_variable_value()

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

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