tf.contrib.learn.DNNClassifier.evaluate()

tf.contrib.learn.DNNClassifier.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.TensorFlowRNNClassifier

class tf.contrib.learn.TensorFlowRNNClassifier TensorFlow RNN Classifier model.

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tf.contrib.learn.BaseEstimator.config

tf.contrib.learn.BaseEstimator.config

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tf.contrib.learn.LinearRegressor.fit()

tf.contrib.learn.LinearRegressor.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.config

tf.contrib.learn.TensorFlowEstimator.config

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tf.contrib.learn.TensorFlowRNNRegressor.fit()

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

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tf.contrib.learn.extract_pandas_matrix()

tf.contrib.learn.extract_pandas_matrix(data) Extracts numpy matrix from pandas DataFrame. Args:

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tf.contrib.learn.extract_dask_labels()

tf.contrib.learn.extract_dask_labels(labels) Extract data from dask.Series for labels.

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tf.contrib.learn.LinearRegressor.get_params()

tf.contrib.learn.LinearRegressor.get_params(deep=True) Get parameters for this estimator. Args:

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tf.contrib.learn.TensorFlowRNNClassifier.

tf.contrib.learn.TensorFlowRNNClassifier.__repr__()

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