This article aims to present the reader to the current workings of the Accord.NET Machine Learning Framework; show where the sequences classifiers are located within the framework, describe their source code, how the Markov namespace is organized and the general ideas behind this organization. This will also provide the base to talk about Hidden Conditional Random Fields, which is my main goal in this series.
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using System;
using System.Drawing;
using System.Windows.Forms;
namespace Gestures.Native
{
/// <summary>
/// Managed wrapper around native methods.
/// </summary>
///
public static class SafeNativeMethods
{
/// <summary>
/// Extends the window frame into the client area.
/// </summary>
///
/// <param name="window">
/// The handle to the window in which the frame will
/// be extended into the client area.</param>
/// <param name="margins">
/// A pointer to a <see cref="ThemeMargins"/> structure that describes
/// the margins to use when extending the frame into the client area.</param>
///
public static void ExtendAeroGlassIntoClientArea(IWin32Window window, ThemeMargins margins)
{
if (window == null) throw new ArgumentNullException("window");
NativeMethods.DwmExtendFrameIntoClientArea(window.Handle, ref margins);
}
/// <summary>
/// Obtains a value that indicates whether Desktop
/// Window Manager (DWM) composition is enabled.
/// </summary>
///
public static bool IsAeroEnabled
{
get { return NativeMethods.DwmIsCompositionEnabled(); }
}
}
}
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Computer and technology enthusiast, interested in artificial intelligence and image processing. Has a Master's degree on Computer Science specialized on Image and Signal Processing, with expertise on Machine Learning, Computer Vision, Pattern Recognition and Data Mining systems. Author of the
Accord.NET Framework for developing scientific computing applications.
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