Titlebook: Data Analytics; Models and Algorithm Thomas A. Runkler Textbook 20162nd edition Springer Fachmedien Wiesbaden 2016 data mining.knowledge di

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书目名称Data Analytics影响因子(影响力)




书目名称Data Analytics影响因子(影响力)学科排名




书目名称Data Analytics网络公开度




书目名称Data Analytics网络公开度学科排名




书目名称Data Analytics被引频次




书目名称Data Analytics被引频次学科排名




书目名称Data Analytics年度引用




书目名称Data Analytics年度引用学科排名




书目名称Data Analytics读者反馈




书目名称Data Analytics读者反馈学科排名

Mirage

Clustering,Complex relational clusters can be found by kernelization. Cluster tendency assessment finds out if the data contain clusters at all, and cluster validity measures help identify an appropriate number of clusters. Clustering can also be done by heuristic methods such as the self-organizing map.

Iatrogenic

AIL

Data and Relations,rlap, Dice, Jaccard, Tanimoto). Sequences can be analyzed using sequence relations (like Hamming, Levenshtein, edit distance). Data can be extracted from continuous signals by sampling and quantization. The Nyquist condition allows sampling without loss of information.

决定性

Data Preprocessing, different effectiveness and computational complexities: moving statistical measures, discrete linear filters, finite impule response, infinite impulse response. Data features with different ranges often need to be standardized or transformed.

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grandiose

Classification,are presented in detail: the naive Bayes classifier, linear discriminant analysis, the support vector machine (SVM) using the kernel trick, nearest neighbor classifiers, learning vector quantification, and hierarchical classification using regression trees.

CANDY

ment data analytics solutions for real-world applications. This book has been used for more than ten years in the Data Mining course at the Technical University of Munich. Much of the content is based on the results of industrial research and development projects at Siemens.978-3-658-14075-5

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