Data mining with spss modeler, theory, exercises and solutions
Wendler, Tilo
Data mining with spss modeler : theory, exercises and solutions [Documento eletrónico] / by Tilo Wendler, Sören Gröttrup. - 2nd ed. . - Cham : Springer , 2021 . - XV, 1274 p. : il.. Now in its second edition, this textbook introduces readers to the IBM SPSS Modeler and guides them through data mining processes and relevant statistical methods. Focusing on step-by-step tutorials and well-documented examples that help demystify complex mathematical algorithms and computer programs, it also features a variety of exercises and solutions, as well as an accompanying website with data sets and SPSS Modeler streams. While intended for students, the simplicity of the Modeler makes the book useful for anyone wishing to learn about basic and more advanced data mining, and put this knowledge into practice. This revised and updated second edition includes a new chapter on imbalanced data and resampling techniques as well as an extensive case study on the cross-industry standard process for data mining.
Clicar aqui para aceder a um recurso externo
ISBN 978-3-030-54338-9
Mathematical statistics
Data mining
Statistics
Computer software
LCC QA276.4-.45
Data mining with spss modeler : theory, exercises and solutions [Documento eletrónico] / by Tilo Wendler, Sören Gröttrup. - 2nd ed. . - Cham : Springer , 2021 . - XV, 1274 p. : il.. Now in its second edition, this textbook introduces readers to the IBM SPSS Modeler and guides them through data mining processes and relevant statistical methods. Focusing on step-by-step tutorials and well-documented examples that help demystify complex mathematical algorithms and computer programs, it also features a variety of exercises and solutions, as well as an accompanying website with data sets and SPSS Modeler streams. While intended for students, the simplicity of the Modeler makes the book useful for anyone wishing to learn about basic and more advanced data mining, and put this knowledge into practice. This revised and updated second edition includes a new chapter on imbalanced data and resampling techniques as well as an extensive case study on the cross-industry standard process for data mining.
Clicar aqui para aceder a um recurso externo
ISBN 978-3-030-54338-9
Mathematical statistics
Data mining
Statistics
Computer software
LCC QA276.4-.45
