The program implements three large-margin thresholded ensemble
algorithms for ordinal regression. It includes an improved RankBoost
algorithm, the ORBoost-LR algorithm, and the ORBoost-All algorithm.
Displaying a large bitmap file on a dialog box, in its original size, is quite difficult in the VC++ environment. However, it is possible to display a large bitmap to a predefined area of the dialog by using the StretchBlt( ) function.The major disadvantage of this is that the clarity of the image will be lost. Check out this article for displaying large bitmaps into the desired area of your dialog box in its original size with a scrolling technique used to show the entire bitmap. 滾動顯示位圖 在VC++環(huán)境下，在一個對話框中顯示一個原始尺寸的大小的位圖文件相當是困難的。然而,通過使用 StretchBlt()函數(shù)一個給定的區(qū)域顯示一個大的位圖是可能的。主要的缺點是圖像將會失真。看了這篇通過卷動技術(shù)顯示整個位圖技術(shù)的文章，你將能夠以它的原始尺寸在給定對話框的區(qū)域內(nèi)顯示一個大位圖。 來源: http://www.codeguru.com/bitmap/ScrollBitmap.html
Displaying large amounts of technical data in a chart can be a frustrating task. You can find tons of charting controls with fancy effects and useless features, but when it comes to displaying many curves at once, independently scaled on different axes, most of them fail.
Software Engineering is a discipline applied by teams to produce high-quality, large-scale, cost-effective software that satisfies the users’ needs, and can be maintained over time
Software Development is a weaker term where standards, tools, processes, etc. may not be applied
support vector classification machine
％ soft margin
％ uses "kernel.m"
％
％ xtrain: (Ltrain,N) with Ltrain: number of points N: dimension
％ ytrain: (Ltrain,1) containing class labels (-1 or +1)
％ xrun: (Lrun,N) with Lrun: number of points N: dimension
％ atrain: alpha coefficients (from svcm_train on xtrain and ytrain)
％ btrain: offest coefficient (from svcm_train on xtrain and ytrain)
％
％ ypred: predicted y (Lrun,1) containing class labels (-1 or +1)
％ margin: (signed) separation from the separating hyperplane (Lrun,1
Overview
Provides a way to store very large collections of email addresses (100,000+ addresses) and efficiently check whether a specific address is contained in a collection. The collection can be created programmatically, or through a pluggable persistence mechanism.
Functionality
Maintains large collections of email addresses.
Efficiently checks whether an address is in the collection or not.
The Bayesian Committee Machine (BCM) is an approximation method for
large-scale Gaussian process regression.
- The code is for Matlab
Version 1.0, November 2005
