map_inits: map_inits: Identifies initial values for optimal Exposure...

In johnlpearce/ECM: ECM: Exposure Continuum Mapping

Description

map_inits: Identifies initial values for optimal Exposure Continuum Map fit via SOM

Usage

map_inits(
  trn_dat,
  xdim = 4,
  ydim = 3,
  maptopo = NULL,
  itermax = NULL,
  seedopt = "pca.sample",
  seedeval = "KL",
  distmet = NULL,
  nstarts = NULL,
  lmode = NULL
)

Arguments

trn_dat	is a data object to map. Should be a numerical or factor based data matrix.
xdim	is x-dimension of the SOM
ydim	is y-dimension of the SOM
maptopo	specifies the topology of the SOM grid as either "rectangular" or "hexagonal"
itermax	specifies the number if learning iterations
seedopt	specifies method for initialization values. "pca.sample", "pca" or "ran" accepted.
seedeval	specifies the evaluation statistic for seed optimalization.
distmet	specifies dissimilarity metric. Current options include "sumofsquares", "euclidean", "manhattan", and "tanimoto". Default is to use "Euclidean" for continuous data, and "tanimoto" for factors.
nstarts	specifies number of initialization schemes to test if inits are not provided
lmode	specifies the learning algorithm. The default is "online" but "batch" and "pbatch" are available via kohonen

Value

a data.frame containing evaluation measures

johnlpearce/ECM documentation built on Dec. 21, 2021, 2:13 a.m.