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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書目名稱Data Mining影響因子(影響力)




書目名稱Data Mining影響因子(影響力)學(xué)科排名




書目名稱Data Mining網(wǎng)絡(luò)公開度




書目名稱Data Mining網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Data Mining被引頻次




書目名稱Data Mining被引頻次學(xué)科排名




書目名稱Data Mining年度引用




書目名稱Data Mining年度引用學(xué)科排名




書目名稱Data Mining讀者反饋




書目名稱Data Mining讀者反饋學(xué)科排名

TEN

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

勉勵

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

CRANK

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

Nutrient

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

有惡臭

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

有惡臭

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

寵愛

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