plot.tf_estimator_history: Plot training history

In tfestimators: Interface to 'TensorFlow' Estimators

Description

Plots metrics recorded during training.

Usage

## S3 method for class 'tf_estimator_history'
plot(
  x,
  y,
  metrics = NULL,
  method = c("auto", "ggplot2", "base"),
  smooth = getOption("tf.estimator.plot.history.smooth", TRUE),
  theme_bw = getOption("tf.estimator.plot.history.theme_bw", FALSE),
  ...
)

Arguments

x	Training history object returned from train().
y	Unused.
metrics	One or more metrics to plot (e.g. c('total_losses', 'mean_losses')). Defaults to plotting all captured metrics.
method	Method to use for plotting. The default "auto" will use ggplot2 if available, and otherwise will use base graphics.
smooth	Whether a loess smooth should be added to the plot, only available for the ggplot2 method. If the number of data points is smaller than ten, it is forced to false.
theme_bw	Use ggplot2::theme_bw() to plot the history in black and white.
...	Additional parameters to pass to the plot() method.

tfestimators documentation built on Aug. 10, 2021, 1:06 a.m.