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<h1>Use provided model object to predict trait values with input dataset</h1>
<small class="dont-index">Source: <a href='https://github.com/GoreLab/waves/blob/master/R/PredictFromSavedModel.R'><code>R/PredictFromSavedModel.R</code></a></small>
<div class="hidden name"><code>PredictFromSavedModel.Rd</code></div>
</div>
<div class="ref-description">
<p>Loads an existing model and cross-validation performance
statistics (created with <code><a href='SaveModel.html'>SaveModel</a></code>) and makes predictions
based on new spectra.</p>
</div>
<pre class="usage"><span class='fu'>PredictFromSavedModel</span><span class='op'>(</span>
<span class='va'>input.data</span>,
<span class='va'>model.stats.location</span>,
<span class='va'>model.location</span>,
wavelengths <span class='op'>=</span> <span class='fl'>740</span><span class='op'>:</span><span class='fl'>1070</span>,
model.method <span class='op'>=</span> <span class='st'>"pls"</span>
<span class='op'>)</span></pre>
<h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
<table class="ref-arguments">
<colgroup><col class="name" /><col class="desc" /></colgroup>
<tr>
<th>input.data</th>
<td><p><code>data.frame</code> object of spectral data for input into a
spectral prediction model. First column contains unique identifiers
followed by spectral columns. Include no other columns to right of spectra!
Column names of spectra must start with "X".</p></td>
</tr>
<tr>
<th>model.stats.location</th>
<td><p>String containing file path (including file name)
to save location of "(model.name)_stats.csv" as output from the SaveModel
function.</p></td>
</tr>
<tr>
<th>model.location</th>
<td><p>String containing file path (including file name) to
location where the trained model ("(model.name).Rds") was saved as output
by the <code><a href='SaveModel.html'>SaveModel</a></code> function.</p></td>
</tr>
<tr>
<th>wavelengths</th>
<td><p>List of wavelengths represented by each column in
<code>input.data</code></p></td>
</tr>
<tr>
<th>model.method</th>
<td><p>Model type to use for training. Valid options include:</p><ul>
<li><p>"pls": Partial least squares regression (Default)</p></li>
<li><p>"rf": Random forest</p></li>
<li><p>"svmLinear": Support vector machine with linear
kernel</p></li>
<li><p>"svmRadial": Support vector machine with radial kernel</p></li>
</ul></td>
</tr>
</table>
<h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
<p><code>data.frame</code> object of predictions for each sample (row). First
column is unique identifier supplied by <code>input.data</code> and second is
predicted values</p>
<h2 class="hasAnchor" id="author"><a class="anchor" href="#author"></a>Author</h2>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><div class='input'><span class='kw'>if</span> <span class='op'>(</span><span class='cn'>FALSE</span><span class='op'>)</span> <span class='op'>{</span>
<span class='va'>ikeogu.2017</span> <span class='op'>%>%</span>
<span class='fu'>dplyr</span><span class='fu'>::</span><span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span><span class='op'>(</span><span class='va'>sample.id</span>, <span class='fu'>dplyr</span><span class='fu'>::</span><span class='fu'><a href='https://tidyselect.r-lib.org/reference/starts_with.html'>starts_with</a></span><span class='op'>(</span><span class='st'>"X"</span><span class='op'>)</span><span class='op'>)</span> <span class='op'>%>%</span>
<span class='fu'>PredictFromSavedModel</span><span class='op'>(</span>input.data <span class='op'>=</span> <span class='va'>.</span>,
model.stats.location <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/paste.html'>paste0</a></span><span class='op'>(</span><span class='fu'><a href='https://rdrr.io/r/base/getwd.html'>getwd</a></span><span class='op'>(</span><span class='op'>)</span>,
<span class='st'>"/my_model_stats.csv"</span><span class='op'>)</span>,
model.location <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/paste.html'>paste0</a></span><span class='op'>(</span><span class='fu'><a href='https://rdrr.io/r/base/getwd.html'>getwd</a></span><span class='op'>(</span><span class='op'>)</span>, <span class='st'>"/my_model.Rds"</span><span class='op'>)</span>,
wavelengths <span class='op'>=</span> <span class='fl'>350</span><span class='op'>:</span><span class='fl'>2500</span><span class='op'>)</span>
<span class='op'>}</span>
</div></pre>
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