SVRModel: Build support vector regression result

In TPMplt: Tool-Kit for Dynamic Materials Model and Thermal Processing Maps

Build support vector regression result

Description

Return a table with continuous values for eta and xi, based on prediction built by support vector regression model (SVR). The kernel function in SVR is radial basis.

Usage

SVRModel(x, seqby = 80)

Arguments

x	The calculation result returned from the function DMMprocess.
seqby	A numeric value to specify the grid density. Default value is 80, namely the default mesh for original plot uses 80*80.

Value

A data frame including continuous values for eta and xi, calculated based on the discrete values for eta and xi returned from DMMprocess. The strain condition in current calculation is also included.

See Also

DMMprocess

Examples

epstable <- epsExtract(TPMdata, 0.7, 2, 3)
DMM <- DMMprocess(epstable)
PLTbd <- SVRModel(DMM)
PLTbd

TPMplt documentation built on Aug. 9, 2025, 1:07 a.m.