Learning Autodesk Maya 2013: A Video Introduction (Wiley, 978-7-4, November 2012, US $79.99)įor additional information about the Sybex Autodesk Learning videos, visit. Learning Autodesk Revit Architecture 2013: A Video Introduction (Wiley, 978-4-3, October 2012, US $79.99).The Sybex Autodesk Learning videos include: Sybex Learning Video courses are available as DVDs or video downloads, come with closed-captioning and work on Macs, PCs, smartphones and tablets. Lessons are presented in immersive, high definition video and the interactive interface lets users quickly navigate to whatever lesson interest them, add custom bookmarks and easily access the related tutorial files. These in-depth video training courses from Sybex and video2brain will help users quickly become proficient in AutoCAD 2013, Autodesk Revit 2013 and Autodesk Maya 2013.Įach video training course features more than seven hours of detailed, step-by-step instruction from leading trainers in the industry who have years of real-world experience using the software. Sybex, an imprint of Wiley, announces a new Learning video series for Autodesk software in collaboration with video2brain, an online video training company. This value is fairly high, which indicates that the model does a good job of classifying the data into ‘Pass’ and ‘Fail’ categories.San Francisco, CA (PRWEB) November 20, 2012 To calculate the AUC of the curve, we can simply take the sum of all of the values in column H: A model with an AUC equal to 0.5 is no better than a model that makes random classifications. The closer AUC is to 1, the better the model. To quantify this, we can calculate the AUC (area under the curve) which tells us how much of the plot is located under the curve. The more that the curve hugs the top left corner of the plot, the better the model does at classifying the data into categories.Īs we can see from the plot above, this logistic regression model does a pretty good job of classifying the data into categories. Then we’ll click the Insert tab along the top ribbon and then click Insert Scatter(X, Y) to create the following plot: To create the ROC curve, we’ll highlight every value in the range F3:G14. We’ll then copy and paste these formulas down to every cell in columns F, G, and H: Next, we’ll calculate the false positive rate (FPR), true positive rate (TPR), and the area under the curve AUC) using the following formulas: Step 3: Calculate False Positive Rate & True Positive Rate We’ll then copy and paste these formulas down to every cell in column D and column E: Next, let’s use the following formula to calculate the cumulative values for the Pass and Fail categories: The following step-by-step example shows how to create and interpret a ROC curve in Excel. This is a plot that displays the sensitivity and specificity of a logistic regression model. One way to visualize these two metrics is by creating a ROC curve, which stands for “receiver operating characteristic” curve. This is also called the “true negative rate.”
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