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Titlebook: Data Mining; 15th Australasian Co Yee Ling Boo,David Stirling,Graham Williams Conference proceedings 2018 Springer Nature Singapore Pte Ltd

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Oil—The Fallout in the Persian Gulfeatures which are more robust to intra-class variation compared to global ones. We gathered a database of 1043 histologic images of neuroblastic tumours classified into five subtypes. Our experiments show the proposed method improves the weighted average F-measure by 1.89% and 0.81% with k-NN and SVM classifiers, respectively.
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Xiaolan Tang,Zhi Geng,Wenlong Chen. In particular, the focus of this study is to identify outlying behaviours amongst providers rather than individual exceptional cases. We propose a new approach that enables identification of outliers on the basis of user defined characteristics.
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Patched Completed Local Binary Pattern is an Effective Method for Neuroblastoma Histological Image Ceatures which are more robust to intra-class variation compared to global ones. We gathered a database of 1043 histologic images of neuroblastic tumours classified into five subtypes. Our experiments show the proposed method improves the weighted average F-measure by 1.89% and 0.81% with k-NN and SVM classifiers, respectively.
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Identifying Precursors to Frequency Fluctuation Events in Electrical Power Generation Datas early indicators of a fluctuation event. Using historical data on known fluctuation events we trained a regression model to estimate the gap between a change point and its corresponding fluctuation point. Our results show that change points could be predicted a number of time steps in advance with a low false alarm rate.
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A Two-Sample Kolmogorov-Smirnov-Like Test for Big Dataion paradigm. The procedure is named the TS-CAKS GoF test. Distributed and streamed implementations of the TS-CAKS procedure are discussed. The consistency of the TS-CAKS test is proved. A numerical study is provided to demonstrate the effectiveness and computational efficiency of the procedure.
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Conference proceedings 2018August 2017..The 17 revised full papers presented together with 11 research track papers and 6 application track papers were carefully reviewed and selected from 31 submissions. The papers are organized in topical sections on clustering and classification; big data; time series; outlier detection an
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