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The pattern recognition applet is perhaps one of the best examples of a Java applet in our library. It is extremely useful for learning about the basics of how data is modeled and classified in a highly interactive environment. The applet allows the user to observe how various pattern recognition algorithms can classify different user-defined data sets. The applet also features an easy-to-user interface and the classification algorithms are performed in a step-by-step mode to make them easier to follow. This tutorial will provide a brief overview of the applet by explaining the menu bar and user interface. Next, follow the apprpriate links to a short tutorial for using each of the classification algorithms. First, let's take a look at the menu bar and the pupose of each menu item. File The ability to Save and Load data sets will be implemented in a later version of the applet. Edit Settings->Set Ranges: Sets the coordinate ranges of the input display panel Settings->Set Gaussian: Sets the characteristics of the Gaussian that can be drawn using the Draw Gaussian feature Settings->Set Class Colors: Sets the color of each data class. Settings->Set Iterations: Sets the number of iterations for the LBG Clustering and K-Means algorithms. Settings->Set Clusters: Sets the number of clusters/centroids for the LBG Clustering Algorithm Clear Input: Clears the contents of the input display panel Clear Output: Clears the contents of the output display panel Clear Display: Clears both the input and output display panels Clear Description: Clears the text in the description panel Clear All: Clears the contents of all panels View Zoom In: Zooms in and focuses on a user defined area. To use: Select Zoom In and click on the desired area of zoom in either the input or output panel. Zoom Out: Zooms out and focuses on a user defined area. To use: Select Zoom Out and click on the desired area of zoom in either the input or output panel Classes These are the four data classes that can be used to construct a data set. Each class is represented by a different color. Patterns Draw Points: Allows single points to be drawn in the input display panel. Use this to construct a data set one point at a time. Draw Gaussian: Allows Gaussian distributions to be drawn or "sprayed" in the input panel. The Gaussian settings can be set from the Edit->Settings->Set Gaussian menu. Preset Patterns:The following are preset input data sets. Selecting any of these will clear the input display panel and display the preset pattern. The following presets are available: Two Gaussian Four Gaussian Overlapping Gaussian Two Ellipses Four Ellipses Rotated Ellipses Toroidal Yin and Yang Algorithms The following is a list of the different classification techniques used in pattern recognition that this applet can demonstrate. Click any of the algorithms below for a detailed description and a brief tutorial. Euclidean Distance Nearest Neighbor K-Means LBG-Clustering Class independent principal component analysis Class dependent principal component analysis Class independent linear discrimination analysis Class dependent linear discrimination analysis SVM: Support Vector Machines RVM: Relevance Vector Machines Go Initialize: Initializes the the selected algorithm with the current input data. Prepares the algorithm for execution. Previous: Executes the previous step of the current classification algorithm. If no previous steps exist, the algorithm will be re-initialized. Next: Executes the next step of the current classification algorithm. If no futher steps exist, a message will be displayed in the Description Box indicating that there are no more steps.