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Titlebook: Business Analytics with R and Python; David L. Olson,Desheng Dash Wu,Majid Nabavi Book 2024 The Editor(s) (if applicable) and The Author(s

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發(fā)表于 2025-3-23 10:09:55 | 只看該作者
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發(fā)表于 2025-3-23 17:28:24 | 只看該作者
The Feminine Voice in PhilosophyCluster analysis is described using the K-means algorithm. Datasets are used to demonstrate cluster analysis representing the important applications of churn, loan application analysis, and real estate evaluation. Rattle is demonstrated on all datasets, with R and Python code provided.
13#
發(fā)表于 2025-3-23 18:02:45 | 只看該作者
https://doi.org/10.1007/978-94-011-3174-2Regression algorithms are described, beginning with simple regression and moving on to autoregressive integrated moving average time series forecasting, multiple regression, stepwise regression, and logistic regression. Rattle is demonstrated on all datasets, with R and Python code provided.
14#
發(fā)表于 2025-3-23 23:50:13 | 只看該作者
15#
發(fā)表于 2025-3-24 05:58:40 | 只看該作者
https://doi.org/10.1007/978-94-011-3174-2The issue of variable selection is presented. Four different machine learning approaches are presented to reduce the number of variables in classification modeling. They are demonstrated with a bankruptcy data file. The value of variable reduction is discussed.
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發(fā)表于 2025-3-24 08:31:25 | 只看該作者
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發(fā)表于 2025-3-24 12:16:43 | 只看該作者
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發(fā)表于 2025-3-24 17:15:42 | 只看該作者
Data Mining Processes,The data mining process from problem identification to study implementation is presented. The major systems (KDD, CRISP-DM and SEMMA) are described. The process of evaluating model results for different types of data is described.
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發(fā)表于 2025-3-24 20:48:39 | 只看該作者
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發(fā)表于 2025-3-24 23:24:33 | 只看該作者
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