plotNN: Create a Plot, Add Lines or Points Depending The Context

In NNbenchmark: Datasets and Functions to Benchmark Neural Network Packages

Description

plotNN uses the parameter uni to launch the plot() function either for a univariate dataset (x, y_pred) or for a multivariate dataset (y, y_pred).

lipoNN uses the parameter uni to launch either lines() for an univariate dataset or points() for a multivariate dataset.

See the examples in prepareZZ.

Usage

plotNN(xory, y0, uni, TF = TRUE, ...)

lipoNN(xory, y_pred, uni, TF = TRUE, ...)

Arguments

xory	vector of numeric. The original x values for an univariate dataset or the original y values for a multivariate dataset.
y0	vector of numeric. The original y values.
uni	logicial. TRUE for an univariate dataset. FALSE for a multivariate dataset. ... fails or if you call the function from another function.
TF	logical. TRUE executes the instruction. FALSE ignores the instruction. Equivalent to if (TRUE/FALSE) plot().
...	parameters passed to plot(), lines() or points().
y_pred	vector of numeric. The values returned by the predict() function.

Value

NULL in the console. An initial plot or some added lines/points.

NNbenchmark documentation built on June 5, 2021, 5:06 p.m.