Titlebook: Intelligent Data Engineering and Automated Learning - IDEAL 2009; 10th International C Emilio Corchado,Hujun Yin Conference proceedings 200

Assemble

FOIL

A Novel Estimation of the Regularization Parameter for ,-SVMoth terms must be optimized in approximately equal conditions in the objective function, we propose to estimate . as a comparison of the new model based on maximums and the standard SVM model. The performance of our approach is shown in terms of SVM training time and test error in several regression problems from well known standard repositories.

Axon895

AMEND

Nearest Neighbor Classification by Relearningod is proposed. The proposed relearning method shows a higher generalization accuracy when compared to the basic kNN with distance function and other conventional learning algorithms. Experiments have been conducted on some benchmark datasets from the UCI Machine Learning Repository.

obnoxious

Mawkish

Lazy Classification Using an Optimized Instance-Based Learnerta mining API, and is available for download. Its performance, according to accuracy and speed metrics, compares relatively well with that of well-established classifiers such as nearest neighbor models or support vector machines. For this reason, the similarity classifier can become a useful instrument in a data mining practitioner’s tool set.

訓誡

CLEFT

FeedRank: A Semantic-Based Management System of Web Feedsal and passive Web feed readers such as: providing only simple presentations of what is received, poor integration of correlated data from different sources, and overwhelming the user with large traffic of feeds that are of no or low interest to them.

BADGE

Jargon

SCIS: Combining Instance Selection Methods to Increase Their Effectiveness over a Wide Range of Domaof methods expected to produce the best results. This approach was evaluated over 20 databases and with six different learning paradigms. The results have been compared with those achieved by five well-known state-of-the-art methods.