df.input

A dataset containing the testdata and other attributes of almost 110
socd030 The variables are as follows:

datasets

Parallel computing, multi-core CPU is used to efficiently compute
and process multi-dimensional soil data.This package includes the
parallelized 'Quantile Regression Forests' algorithm for Digital Soil Mapping
and is mainly dependent on the package 'quantregForest' and 'snowfall'.
Detailed references to the R package and the web site are described in the
methods, as detailed in the method documentation.

Peicong Tang

ParallelDSM

Parallel Digital Soil Mapping using Machine Learning

Xiaodong Song

Wentao Zhu

Gaoqiang Ge

Jun Zhu

Ganlin Zhang

df.input function

A data frame with 109 rows and 6 variables:<dl>
<dt>socd030</dt>
<dd>data variable socd030</dd><dt>dem</dt>
<dd>data variable DEM</dd><dt>plancur</dt>
<dd>data variable plancur</dd><dt>procur</dt>
<dd>data variable procur</dd><dt>mrrtf</dt>
<dd>data variable mrrtf</dd><dt>twi</dt>
<dd>data variable twi</dd>
</dl>

Format

Sampling test data — df.input

A data frame with 109 rows and 6 variables:<dl>
<dt>socd030</dt>
<dd>data variable socd030</dd>

<dt>dem</dt>
<dd>data variable DEM</dd>

<dt>plancur</dt>
<dd>data variable plancur</dd>

<dt>procur</dt>
<dd>data variable procur</dd>

<dt>mrrtf</dt>
<dd>data variable mrrtf</dd>

<dt>twi</dt>
<dd>data variable twi</dd>


</dl>

df.input: Sampling test data

Description

Usage

Arguments

Format