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

Obsolescent

書目名稱Discovery Science影響因子(影響力)




書目名稱Discovery Science影響因子(影響力)學科排名




書目名稱Discovery Science網(wǎng)絡(luò)公開度




書目名稱Discovery Science網(wǎng)絡(luò)公開度學科排名




書目名稱Discovery Science被引頻次




書目名稱Discovery Science被引頻次學科排名




書目名稱Discovery Science年度引用




書目名稱Discovery Science年度引用學科排名




書目名稱Discovery Science讀者反饋




書目名稱Discovery Science讀者反饋學科排名

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

倔強一點

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