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	<title>Variable Selection &#8211; NIRPY Research</title>
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	<description>Statistical learning and chemometrics in Python</description>
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	<title>Variable Selection &#8211; NIRPY Research</title>
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		<title>The SPXY algorithm</title>
		<link>https://nirpyresearch.com/spxy-algorithm/</link>
		
		<dc:creator><![CDATA[Daniel Pelliccia]]></dc:creator>
		<pubDate>Sun, 19 Apr 2026 08:56:03 +0000</pubDate>
				<category><![CDATA[Data Operations and Plotting]]></category>
		<category><![CDATA[Test-train split]]></category>
		<category><![CDATA[Variable Selection]]></category>
		<category><![CDATA[cross-validation]]></category>
		<category><![CDATA[distance]]></category>
		<category><![CDATA[kennard-stone]]></category>
		<category><![CDATA[spxy]]></category>
		<category><![CDATA[test-train split]]></category>
		<guid isPermaLink="false">https://nirpyresearch.com/?p=3509</guid>

					<description><![CDATA[<img width="666" height="499" src="https://nirpyresearch.com/wp-content/uploads/2026/01/spxy_nirpy_research.jpg" class="webfeedsFeaturedVisual wp-post-image" alt="Feature image for the SPXY algorithm post" style="display: block; margin-bottom: 10px; clear: both; max-width: 100%;" decoding="async" fetchpriority="high" />SPXY is a deterministic splitting algorithm designed to incorporate information from both spectra and response. It's an extension of the Kennard-Stone method.]]></description>
		
		
		
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		<title>Genetic algorithm for wavelength selection using Numpy</title>
		<link>https://nirpyresearch.com/genetic-algorithm-wavelength-selection-numpy/</link>
		
		<dc:creator><![CDATA[Daniel Pelliccia]]></dc:creator>
		<pubDate>Sat, 22 Jun 2024 09:48:43 +0000</pubDate>
				<category><![CDATA[Regression]]></category>
		<category><![CDATA[Partial Least Squares Regression]]></category>
		<category><![CDATA[Variable Selection]]></category>
		<guid isPermaLink="false">https://nirpyresearch.com/?p=3173</guid>

					<description><![CDATA[<img width="666" height="499" src="https://nirpyresearch.com/wp-content/uploads/2024/06/genetic-algorithm-numpy-nirpy-research.jpg" class="webfeedsFeaturedVisual wp-post-image" alt="genetic algorithm" style="display: block; margin-bottom: 10px; clear: both; max-width: 100%;" decoding="async" />A implementation of a genetic algorithm for wavelength selection using basic Numpy functions.]]></description>
		
		
		
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		<title>Wavelength selection with a genetic algorithm</title>
		<link>https://nirpyresearch.com/wavelength-selection-genetic-algorithm/</link>
		
		<dc:creator><![CDATA[Daniel Pelliccia]]></dc:creator>
		<pubDate>Fri, 28 Jul 2023 10:33:22 +0000</pubDate>
				<category><![CDATA[Data Operations and Plotting]]></category>
		<category><![CDATA[Partial Least Squares Regression]]></category>
		<category><![CDATA[Regression]]></category>
		<category><![CDATA[Variable Selection]]></category>
		<guid isPermaLink="false">https://nirpyresearch.com/?p=3028</guid>

					<description><![CDATA[<img width="666" height="499" src="https://nirpyresearch.com/wp-content/uploads/2023/07/Wavelength-selection-genetic-algorithm-nirpy-research.jpg" class="webfeedsFeaturedVisual wp-post-image" alt="" style="display: block; margin-bottom: 10px; clear: both; max-width: 100%;" decoding="async" />Wavelength selection methods aim at choosing the spectral bands that produce the best regression or classification model. Here we introduce a genetic algorithm for wavelength selection.]]></description>
		
		
		
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		<title>A variable selection method for PLS in Python</title>
		<link>https://nirpyresearch.com/variable-selection-method-pls-python/</link>
		
		<dc:creator><![CDATA[Daniel Pelliccia]]></dc:creator>
		<pubDate>Tue, 03 Jul 2018 23:20:18 +0000</pubDate>
				<category><![CDATA[Data Operations and Plotting]]></category>
		<category><![CDATA[Partial Least Squares Regression]]></category>
		<category><![CDATA[Regression]]></category>
		<category><![CDATA[Variable Selection]]></category>
		<guid isPermaLink="false">https://www.idtools.com.au/?p=1296</guid>

					<description><![CDATA[<img width="680" height="340" src="https://nirpyresearch.com/wp-content/uploads/2018/07/variable-selection-PLS-selected-1024x512.png" class="webfeedsFeaturedVisual wp-post-image" alt="A variable selection method for PLS in Python" style="display: block; margin-bottom: 10px; clear: both; max-width: 100%;" decoding="async" loading="lazy" />Improve the quality of your PLS regression using variable selection. This tutorial will work through a variable selection method for PLS in Python.]]></description>
		
		
		
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