tfestimators

Boosted Trees Estimator

Generates Parsing Spec for TensorFlow Example to be Used with Classifiers

Establish a Feature Columns Selection Scope

Base Documentation for Feature Column Constructors

Construct a Bucketized Column

Construct a Weighted Categorical Column

Represents Sparse Feature where IDs are set by Hashing

Construct a Categorical Column that Returns Identity Values

Construct a Categorical Column with a Vocabulary File

Construct a Categorical Column with In-Memory Vocabulary

Construct a Crossed Column

Construct a Dense Column

Represents Multi-Hot Representation of Given Categorical Column

Construct a Real-Valued Column

Deep Neural Networks

Linear Combined Deep Neural Networks

Construct a Custom Estimator

Define an Estimator Specification

Base Documentation for Canned Estimators

Configuration for the eval component of train_and_evaluate

Evaluate an Estimator

Construct an Experiment

Save an Estimator

Feature Columns

Standard Names to Use for Graph Collections

Saves Checkpoints Every N Steps or Seconds

Delay Execution until Global Step Reaches to wait_until_step.

A Custom Run Hook for Saving Metrics History

Prints Given Tensors Every N Local Steps, Every N Seconds, or at End

NaN Loss Monitor

A Custom Run Hook to Create and Update Progress Bar During Training or Evaluation

Steps per Second Monitor

Monitor to Request Stop at a Specified Step

Saves Summaries Every N Steps

Construct an Input Function

Construct an Input Layer

Keras Estimators

Get the Latest Checkpoint in a Checkpoint Directory

Construct a Linear Estimator

Canonical Metric Keys

Canonical Mode Keys

Model directory

Construct Input Function Containing Python Dictionaries of Numpy Arrays

Plot training history

Generate Predictions with an Estimator

Canonical Model Prediction Keys

Objects exported from other packages

Generates Parsing Spec for TensorFlow Example to be Used with Regressors

Run Configuration

Create Session Run Arguments

Create Custom Session Run Hooks

Task Types

High-level Estimator API in TensorFlow for R

Base Documentation for train, evaluate, and predict.

Train an Estimator

Train and evaluate the estimator.

Configuration for the train component of train_and_evaluate

Get variable names and values associated with an estimator