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Titlebook: Data Analytics; Models and Algorithm Thomas A. Runkler Textbook 20203rd edition Springer Fachmedien Wiesbaden GmbH, part of Springer Nature

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Data and Relations,p, Dice, Jaccard, Tanimoto). Sequences can be analyzed using sequence relations (like Hamming or 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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Correlation,elation can also be quantified by the cross-validation error of regression models. Correlation does not imply causality. Spurious correlations may lead to wrong conclusions. If the underlying features are known, then spurious correlations may be compensated by partial correlation methods.
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Circularity Assessment: Macro to Nano data, often enhanced by kernelization. Cluster tendency assessment finds out if the data contain clusters at all, and cluster validity measures help identify the number of clusters or other algorithmic parameters. Clustering can also be done by heuristic methods such as self-organizing maps.
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Clustering, data, often enhanced by kernelization. Cluster tendency assessment finds out if the data contain clusters at all, and cluster validity measures help identify the number of clusters or other algorithmic parameters. Clustering can also be done by heuristic methods such as self-organizing maps.
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