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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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书目名称Data Mining
副标题15th Australasian Co
编辑Yee Ling Boo,David Stirling,Graham Williams
视频video
丛书名称Communications in Computer and Information Science
图书封面Titlebook: Data Mining; 15th Australasian Co Yee Ling Boo,David Stirling,Graham Williams Conference proceedings 2018 Springer Nature Singapore Pte Ltd
描述.This book constitutes the refereed proceedings of the 15th Australasian Conference on Data Mining, AusDM 2017, held in Melbourne, VIC, Australia, in August 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 and applications; social media and applications..
出版日期Conference proceedings 2018
关键词artificial intelligence; classification; data mining; decision trees; machine learning; signal processing
版次1
doihttps://doi.org/10.1007/978-981-13-0292-3
isbn_softcover978-981-13-0291-6
isbn_ebook978-981-13-0292-3Series ISSN 1865-0929 Series E-ISSN 1865-0937
issn_series 1865-0929
copyrightSpringer Nature Singapore Pte Ltd. 2018
The information of publication is updating

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Rank Forest: Systematic Attribute Sub-spacing in Decision Forestjor shortcomings of decision trees have been pointed out: (1) instability, and (2) high computational cost. These problems have been addressed to some extent through ensemble learning techniques such as Random Forest. Unlike decision trees where the whole attribute space of a dataset is used to disc
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Performance Evaluation of a Distributed Clustering Approach for Spatial Datasetsnot have as a whole. Therefore, new data analytics frameworks are needed to deal with the big data challenges such as volumes, velocity, veracity, variety of the data. Distributed data mining constitutes a promising approach for big data sets, as they are usually produced in distributed locations, a
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Patched Completed Local Binary Pattern is an Effective Method for Neuroblastoma Histological Image C existing computer-aided histological image classification methods that use global features. To tackle this problem, we propose a new Patched Completed Local Binary Pattern (PCLBP) method combining Sign Binary Pattern (SBP) and Magnitude Binary Pattern (MBP) within local patches to build feature vec
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An Improved Naive Bayes Classifier-Based Noise Detection Technique for Classifying User Phone Call B outgoing), with many potential negative consequences. The classification accuracy may decrease and the complexity of the classifiers may increase due to the number of redundant training samples. To detect such noisy instances from a training dataset, researchers use naive Bayes classifier (NBC) as
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A Two-Sample Kolmogorov-Smirnov-Like Test for Big Datauseful EDA tools impractical and ineffective. Among such useful tools is the two-sample Kolmogorov-Smirnov (TS-KS) goodness-of-fit (GoF) test for assessing whether or not two samples arose from the same population. A TS-KS like testing procedure is constructed using chunked and averaged (CA) estimat
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Exploiting Redundancy, Recurrency and Parallelism: How to Link Millions of Addresses with Ten Lines ked social problems are best tackled by forming partnerships founded on large-scale data fusion. Names and addresses are the most common attributes on which data from different government agencies can be linked. In this paper, we focus on the problem of address linking. Linkage is particularly probl
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