an introduction of C Program by sunner sun of HIT .
标签: introduction Program sunner of
上传时间: 2016-01-27
上传用户:星仔
This will show you how to texture a background in DirectX THis was brought to you by Lost Side Dead
标签: background you DirectX brought
上传时间: 2016-01-28
上传用户:cmc_68289287
开源投影系统 Cartographic Projections library originally written by Gerald Evenden then of the USGS. The primary version of this web page can be found at http://www.remotesensing.org/proj, and mirrored at http://proj.maptools.org.
标签: Cartographic Projections originally Evenden
上传时间: 2016-01-28
上传用户:zhouchang199
This the second tutorial of the Writing Device Drivers series. There seems to be a lot of interest in the topic, so this article will pick up where the first left off. The main focus of these articles will be to build up little by little the knowledge needed to write device drivers. In this article, we will be building on the same example source code used in part one. In this article, we will expand on that code to include Read functionality, Handle Input/Ouput Controls also known as IOCTLs, and learn a bit more about IRPs.
标签: the interest tutorial Drivers
上传时间: 2016-01-28
上传用户:lmeeworm
By the proof of Lemma 2 of Section 5.2, this accomplished as follows:
标签: accomplished Section follows proof
上传时间: 2014-01-27
上传用户:璇珠官人
By the proof of Lemma 2 of Section 5.2, this accomplished as follows:
标签: accomplished Section follows proof
上传时间: 2016-01-29
上传用户:wlcaption
By the proof of Lemma 2 of Section 5.2, this accomplished as follows:
标签: accomplished Section follows proof
上传时间: 2013-12-18
上传用户:66666
An object based tree widget, emulating the one found in microsoft windows, | | with persistence using cookies. Works in IE 5+, Mozilla and konqueror 3.
标签: persistence emulating microsoft windows
上传时间: 2016-01-30
上传用户:qiao8960
Boosting is a meta-learning approach that aims at combining an ensemble of weak classifiers to form a strong classifier. Adaptive Boosting (Adaboost) implements this idea as a greedy search for a linear combination of classifiers by overweighting the examples that are misclassified by each classifier. icsiboost implements Adaboost over stumps (one-level decision trees) on discrete and continuous attributes (words and real values). See http://en.wikipedia.org/wiki/AdaBoost and the papers by Y. Freund and R. Schapire for more details [1]. This approach is one of most efficient and simple to combine continuous and nominal values. Our implementation is aimed at allowing training from millions of examples by hundreds of features in a reasonable time/memory.
标签: meta-learning classifiers combining Boosting
上传时间: 2016-01-30
上传用户:songnanhua
Essential C++ By Stanley B. Lippman Publisher : Addison Wesley Pub Date : September 12, 2002 ISBN : 0-201-48518-4 Pages : 416
标签: B. Essential Publisher September
上传时间: 2016-01-30
上传用户:zhengjian