title: "Plotting Keras Performance Trajectories"

author: "John Mount"

date: "`r Sys.Date()`"

output:

tufte::tufte_html: default

tufte::tufte_handout:

citation_package: natbib

latex_engine: xelatex

tufte::tufte_book:

citation_package: natbib

latex_engine: xelatex

link-citations: yes

Below is the standard performance trajectory plot from `Keras`.

```{r setup}

We can also load the `Keras` `metricsframe` (a `data.frame` that is fairly standard to when working with `Keras`) and demonstrate or new [`WVPlots::plot_Keras_fit_trajectory()`](https://winvector.github.io/WVPlots/reference/plot_Keras_fit_trajectory.html) plot.

```{r wvplots}

Obviously this plot needs some training to interpret, but that is pretty much the case for all visualizations.

The ideas of this plot include:

* All facets have the same interpretation: "up is better." This makes it easier to relate the shapes in one pane to the other.

* The only horizontal solid curve rendered is the validation (or hold-out) performance. The validation performance is the primary item of interest, so it gets a unique presentation.

* The training performance is represented as the upper boundary of the shaded region and with the pluses and vertical strokes.

* A vertical line is added at the best epoch picked by the "minus binary cross entropy" metric (this can be turned off or changed).

* An optional additional training over-fit penalized dashed curve is added. The default is: this is the validation score minus `10%` of the excess generalization error (the difference in training and validation performance).