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	<title>Machine Learning Archives &#8212; MATLAB Number ONE</title>
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	<description>MATLAB Simulink &#124; Tutorial &#124; Code &#124; Project</description>
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	<title>Machine Learning Archives &#8212; MATLAB Number ONE</title>
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		<title>Wavelet Neural Network in MATLAB</title>
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		<pubDate>Sun, 02 Aug 2020 11:58:18 +0000</pubDate>
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					<description><![CDATA[<p>An educational video has been prepared on how to implement Wavelet Neural Network in MATLAB, which shows in a simple and step-by-step manner both methods of implementing Wavelet Neural Network in MATLAB.  There are two methods for implementing the wavelet neural network, Both methods are educated in this video tutorial. In some applications, such as [&#8230;]</p>
<p>The post <a href="https://matlab1.com/shop/matlab-video/wavelet-neural-network-in-matlab/">Wavelet Neural Network in MATLAB</a> appeared first on <a href="https://matlab1.com">MATLAB Number ONE</a>.</p>
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		<title>Programming of random forest in MATLAB</title>
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		<dc:creator><![CDATA[global MATLAB]]></dc:creator>
		<pubDate>Sun, 02 Aug 2020 06:12:48 +0000</pubDate>
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					<description><![CDATA[<p>Random forest consists of several decision trees that use input data subsets. Random forest uses averaging to improve prediction accuracy and control overfitting. There are many codes for Random forest on the Internet. We tested most of them and chose one of the best. In this video tutorial, we will explain how to use this [&#8230;]</p>
<p>The post <a href="https://matlab1.com/shop/matlab-video/programming-of-random-forest-in-matlab/">Programming of random forest in MATLAB</a> appeared first on <a href="https://matlab1.com">MATLAB Number ONE</a>.</p>
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		<title>ARIMA modeling in MATLAB</title>
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		<dc:creator><![CDATA[global MATLAB]]></dc:creator>
		<pubDate>Sun, 02 Aug 2020 05:41:51 +0000</pubDate>
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					<description><![CDATA[<p>In statistics and econometrics, and especially in time series analysis, an &#8220;AutoRegressive Integrated Moving Average&#8221; (ARIMA) is a broader model than the AutoRegressive Moving Average (ARMA). These models are used in time series to better understand the model or predict the future. These models are used where the data is non-stationary. In this case, once [&#8230;]</p>
<p>The post <a href="https://matlab1.com/shop/machine-learning/arima-modeling-in-matlab/">ARIMA modeling in MATLAB</a> appeared first on <a href="https://matlab1.com">MATLAB Number ONE</a>.</p>
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