Titlebook: Discovery Science; 13th International C Bernhard Pfahringer,Geoff Holmes,Achim Hoffmann Conference proceedings 2010 Springer Berlin Heidelb

Obsolescent

书目名称Discovery Science影响因子(影响力)




书目名称Discovery Science影响因子(影响力)学科排名




书目名称Discovery Science网络公开度




书目名称Discovery Science网络公开度学科排名




书目名称Discovery Science被引频次




书目名称Discovery Science被引频次学科排名




书目名称Discovery Science年度引用




书目名称Discovery Science年度引用学科排名




书目名称Discovery Science读者反馈




书目名称Discovery Science读者反馈学科排名

Exploit

A Similarity-Based Adaptation of Naive Bayes for Label Ranking: Application to the Metalearning Proe been adapted for this task, including k-Nearest Neighbours (k-NN) and decision trees. Following this line, we propose an adaptation of the naive Bayes classification algorithm for the label ranking problem. Our main idea lies in the use of similarity between the rankings to replace the concept of

半身雕像

Topology Preserving SOM with Transductive Confidence Machine,dimension reduction tool for mapping training samples from a high-dimensional input space onto a neuron grid. However, current SOM-based classifiers can not provide degrees of classification reliability for new unlabeled samples so that they are difficult to be used in risk-sensitive applications wh

Invertebrate

An Artificial Experimenter for Enzymatic Response Characterisation, comparison to the size of the parameter spaces being investigated. New tools are required to assist scientists in the effective characterisation of such behaviours. By combining artificial intelligence techniques for active experiment selection, with a microfluidic experimentation platform that red

Hdl348

Subgroup Discovery for Election Analysis: A Case Study in Descriptive Data Mining, of election results. Our inquiry is based on the 2009 German federal Bundestag election (restricted to the City of Cologne) and additional socio-economic information about Cologne’s polling districts. The task is to describe relations between socio-economic variables and the votes in order to summa

ECG769

ECG769

seroma

倔强一点

Incremental Learning of Cellular Automata for Parallel Recognition of Formal Languages,rning of one-dimensional, bounded, one-way, cellular automata (OCAs) that recognize formal languages from positive and negative sample strings. The objectives of this work are to develop automatic synthesis of parallel systems and to contribute to the theory of real-time recognition by cellular auto

Hyperalgesia

Sparse Substring Pattern Set Discovery Using Linear Programming Boosting,t margin optimization problem where each dimension corresponds to a substring pattern. Then we solve this problem by using LPBoost and an optimal substring discovery algorithm. Since the problem is a linear program, the resulting solution is likely to be sparse, which is useful for feature selection