tonywjd/

2 OWL Web本体语言指南

tonywjd收录，使用标签：ai, ontology，时间：2008-4-17 21:11:18 | 相关网摘，我也收藏

http://zh.transwiki.org/cn/owlguide.htm

1 Weka 3 - Data Mining with Open Source Machine Learning Software in Java

tonywjd收录，使用标签：Opensource, ai, weka，时间：2008-4-13 13:03:49 | 相关网摘，我也收藏

Weka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classification, regression, clustering, association rules, and visualization. It is also well-suited for developing new machine learning schemes.

Weka is open source software issued under the GNU General Public License.

http://www.cs.waikato.ac.nz/ml/weka/index_home.html

1 SVM-Multiclass: Multi-Class Support Vector Machine

tonywjd收录，使用标签：ai, svm，时间：2008-1-25 16:42:21 | 相关网摘，我也收藏

To solve this optimization problem, SVMmulticlass uses an algorithm that is different from the one in [1]. The algorithm is based on Structural SVMs [2] and it is an instance of SVMstruct. For linear kernels, SVMmulticlass V2.12 is very fast and runtime scales linearly with the number of training examples. Non-linear kernels are not (really) supported. It also serves as a easy tutorial example of how to use the SVMstruct programming interface. More information on SVMstruct is available here.

http://www.cs.cornell.edu/People/tj/svm%5Flight/svm_multiclass.html

1 SVM-Light Support Vector Machine

tonywjd收录，使用标签：ai, svm，时间：2008-1-24 10:29:20 | 相关网摘，我也收藏

SVMlight is an implementation of Support Vector Machines (SVMs) in C. The main features of the program are the following:

fast optimization algorithm
working set selection based on steepest feasible descent
"shrinking" heuristic
caching of kernel evaluations
use of folding in the linear case
solves classification and regression problems. For multivariate and structured outputs use SVMstruct.
solves ranking problems (e. g. learning retrieval functions in STRIVER search engine).
computes XiAlpha-estimates of the error rate, the precision, and the recall
efficiently computes Leave-One-Out estimates of the error rate, the precision, and the recall
includes algorithm for approximately training large transductive SVMs (TSVMs) (see also Spectral Graph Transducer)
can train SVMs with cost models and example dependent costs
allows restarts from specified vector of dual variables
handles many thousands of support vectors
handles several hundred-thousands of training examples
supports standard kernel functions and lets you define your own
uses sparse vector representation

http://www.cs.cornell.edu/People/tj/svm%5Flight/

1 University of Dortmund -- Computer Science VIII

tonywjd收录，使用标签：ai, svm，时间：2008-1-24 10:28:55 | 相关网摘，我也收藏

mySVM is an implementation of the Support Vector Machine introduced by V. Vapnik (see [Vapnik/98a]). It is based on the optimization algorithm of SVMlight as described in [Joachims/99a]. mySVM can be used for pattern recognition, regression and distribution estimation.

http://www-ai.cs.uni-dortmund.de/SOFTWARE/MYSVM/index.html

1 迷失星空

tonywjd收录，使用标签：ai, ml，时间：2007-12-11 15:29:53 | 相关网摘，我也收藏

流形学习是个很广泛的概念。这里我主要谈的是自从2000年以后形成的流形学习概念和其主要代表方法。自从2000年以后，流形学习被认为属于非线性降维的一个分支。众所周知，引导这一领域迅速发展的是2000年Science杂志上的两篇文章: Isomap and LLE (Locally Linear Embedding)。

http://ranjie.mobile.spaces.live.com/ent.aspx?h=cns!EF3F252267045AB7!558&fp=%2fent.aspx