Titlebook: Machine Learning and Data Mining in Pattern Recognition; 10th International C Petra Perner Conference proceedings 2014 Springer Internation

Proponent

acrobat

Lecture Notes in Computer Sciencehttp://image.papertrans.cn/m/image/620467.jpg

Pillory

A Cost-Sensitive Based Approach for Improving Associative Classification on Imbalanced Datasetsta. SSCR combines statistically significant association rules with cost-sensitive learning to build an associative classifier. Experimental results show that SSCR achieves best performance in terms of true positive rate and recall on real-world imbalanced datasets, compared with CBA and C4.5.

fertilizer

A Novel Approach for Identifying Banded Patterns in Zero-One Data Using Column and Row Banding Scoreut the need to consider large numbers of permutations. This mechanism has been incorporated into the Banded Pattern Mining (BPM) algorithm proposed in this paper. The operation of BPM is fully discussed. A Complete evaluation of the BPM algorithm is also presented clearly indicating the advantages o

漂泊

ACCD: Associative Classification over Concept-Drifting Data Streamsthm over data streams), AUEH (Accuracy updated ensemble with Hoeffding tree) and VFDT(Very Fast Decision Trees) on 4 real-world data stream datasets, ACCD exhibits the best performance in terms of accuracy.

flutter

高深莫測(cè)

Monitoring Distributed Data Streams through Node Clusteringempt to collect together similar data items, monitoring requires clusters with . vectors canceling each other as much as possible. In particular, sub–clusters of a good cluster do not have to be good. This novel type of clustering dictated by the problem at hand requires development of new algorithm

Hiatus

blight

exercise