Abstract
Having characterised the problem that we address and the way of acquiring data that we use, we now turn to the features, which can be extracted from the raw data, and the choice of the possibly good selection of a subset of these variables from the point of view of the problem at hand.
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Notes
- 1.
Although the character of the variables considered in this study is quite diversified, Pearson’s correlation coefficient was used throughout as best fitted to all the different cases we analysed.
- 2.
See Model Prediction Correlation Heatmap—h2o.model_correlation_heatmap.h2o (https://docs.h2o.ai/h2o/latest-stable/h2o-r/docs/reference/h2o.model_correlation_heatmap.html).
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Jastrzębska, A. et al. (2023). The Proper Representation: Patterns, Variables and Their Analysis. In: Analysing Web Traffic. Studies in Big Data, vol 127. Springer, Cham. https://doi.org/10.1007/978-3-031-32503-8_3
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DOI: https://doi.org/10.1007/978-3-031-32503-8_3
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