sits_rfor: Train SITS classifiction models

In luizassis/sits: Satellite Image Time Series Analysis

Description

Use Random Forest algorithm to classify data. This function is a front-end to the "randomForest" method in the "randomForest" package. Please refer to the documentation in that package for more details.

Usage

sits_rfor(distances.tb = NULL, ntree = 500, ...)

Arguments

distances.tb	a time series with a set of distance measures for each training sample
ntree	Number of trees to grow. This should not be set to too small a number, to ensure that every input row gets predicted at least a few times. (default: 500)
...	other parameters to be passed to 'randomForest::randomForest' function

Value

result either an model function to be passed in sits_predict or an function prepared that can be called further to compute multinom training model

Author(s)

Alexandre Xavier Ywata de Carvalho, [e-mail]

Rolf Simoes, [e-mail]

luizassis/sits documentation built on May 30, 2019, 7:15 p.m.