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

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書目名稱Data Analytics影響因子(影響力)




書目名稱Data Analytics影響因子(影響力)學(xué)科排名




書目名稱Data Analytics網(wǎng)絡(luò)公開度




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




書目名稱Data Analytics被引頻次




書目名稱Data Analytics被引頻次學(xué)科排名




書目名稱Data Analytics年度引用




書目名稱Data Analytics年度引用學(xué)科排名




書目名稱Data Analytics讀者反饋




書目名稱Data Analytics讀者反饋學(xué)科排名

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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.

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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.

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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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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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