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Categorical Variable - Crossref

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Last Updated: 10 January 2023

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Categorical Variable Mapping Considerations in Classification Problems: Protein Application

In machine learning classification problems, the transformation of categorical variables into numerical values is common. Using amino acid data, we present a series of four possible interpretations of these maps in the context of protein classification. This assumption involves the conversion of categorical variables into protein classification problems without the need to use techniques such as natural language processing. The numerical simulations are shown that the numerical results are consistent with the original research findings, such as translation and permutations, and that the eigenvalue approach generates classifications that are not consistent with the base case or have higher mean values, while still delivering some benefits such as having a predetermined number regardless of the analyzed protein's size.

Source link: https://doi.org/10.3390/math11020279


Categorical Variable Problem In Real Estate Submarket Determination With Gwr Model

Abstract The property market review can include several aspects. Estimating GWR models is either extremely difficult or impossible, as neighborhoods of individual homes can be very uneven in terms of some variables. The study will present an approach in which the categorical variables are converted into a single synthetic variable, and only this variable will be used to determine the explanatory variable in the model. The aim of this paper is to identify the boundaries of submarkets in the study area and compare the results of modeling the value of real estate using methods that do not consider local markets, as well as ones that incorporate local markets identified by experts and using the GWR model.

Source link: https://doi.org/10.2478/remav-2022-0028

* Please keep in mind that all text is summarized by machine, we do not bear any responsibility, and you should always check original source before taking any actions

* Please keep in mind that all text is summarized by machine, we do not bear any responsibility, and you should always check original source before taking any actions