Man pages for rstudio/tflearn
Interface to 'TensorFlow' Estimators
| boosted_trees_estimators | Boosted Trees Estimator |
| classifier_parse_example_spec | Generates Parsing Spec for TensorFlow Example to be Used with... |
| column_base | Base Documentation for Feature Column Constructors |
| column_bucketized | Construct a Bucketized Column |
| column_categorical_weighted | Construct a Weighted Categorical Column |
| column_categorical_with_hash_bucket | Represents Sparse Feature where IDs are set by Hashing |
| column_categorical_with_identity | Construct a Categorical Column that Returns Identity Values |
| column_categorical_with_vocabulary_file | Construct a Categorical Column with a Vocabulary File |
| column_categorical_with_vocabulary_list | Construct a Categorical Column with In-Memory Vocabulary |
| column_crossed | Construct a Crossed Column |
| column_embedding | Construct a Dense Column |
| column_indicator | Represents Multi-Hot Representation of Given Categorical... |
| column_numeric | Construct a Real-Valued Column |
| column-scope | Establish a Feature Columns Selection Scope |
| dnn_estimators | Deep Neural Networks |
| dnn_linear_combined_estimators | Linear Combined Deep Neural Networks |
| estimator | Construct a Custom Estimator |
| estimators | Base Documentation for Canned Estimators |
| estimator_spec | Define an Estimator Specification |
| eval_spec | Configuration for the eval component of 'train_and_evaluate' |
| evaluate.tf_estimator | Evaluate an Estimator |
| experiment | Construct an Experiment |
| export_savedmodel.tf_estimator | Save an Estimator |
| feature_columns | Feature Columns |
| graph_keys | Standard Names to Use for Graph Collections |
| hook_checkpoint_saver | Saves Checkpoints Every N Steps or Seconds |
| hook_global_step_waiter | Delay Execution until Global Step Reaches to... |
| hook_history_saver | A Custom Run Hook for Saving Metrics History |
| hook_logging_tensor | Prints Given Tensors Every N Local Steps, Every N Seconds, or... |
| hook_nan_tensor | NaN Loss Monitor |
| hook_progress_bar | A Custom Run Hook to Create and Update Progress Bar During... |
| hook_step_counter | Steps per Second Monitor |
| hook_stop_at_step | Monitor to Request Stop at a Specified Step |
| hook_summary_saver | Saves Summaries Every N Steps |
| input_fn | Construct an Input Function |
| input_layer | Construct an Input Layer |
| keras_model_to_estimator | Keras Estimators |
| latest_checkpoint | Get the Latest Checkpoint in a Checkpoint Directory |
| linear_estimators | Construct a Linear Estimator |
| metric_keys | Canonical Metric Keys |
| mode_keys | Canonical Mode Keys |
| model_dir | Model directory |
| numpy_input_fn | Construct Input Function Containing Python Dictionaries of... |
| plot.tf_estimator_history | Plot training history |
| prediction_keys | Canonical Model Prediction Keys |
| predict.tf_estimator | Generate Predictions with an Estimator |
| reexports | Objects exported from other packages |
| regressor_parse_example_spec | Generates Parsing Spec for TensorFlow Example to be Used with... |
| run_config | Run Configuration |
| session_run_args | Create Session Run Arguments |
| session_run_hook | Create Custom Session Run Hooks |
| task_type | Task Types |
| tfestimators | High-level Estimator API in TensorFlow for R |
| train_and_evaluate.tf_estimator | Train and evaluate the estimator. |
| train-evaluate-predict | Base Documentation for train, evaluate, and predict. |
| train_spec | Configuration for the train component of 'train_and_evaluate' |
| train.tf_estimator | Train an Estimator |
| variable_names_values | Get variable names and values associated with an estimator |
