Categorical aggregation case study

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Similarity or distance measures are core components used by distance-based clustering algorithms to cluster similar data points into the same clusters, while dissimilar or distant data points are placed into different clusters. The performance of similarity measures is mostly addressed in two or three-dimensional spaces, beyond which, to the best of our knowledge, there is no empirical study that has revealed the behavior of similarity measures when dealing with high-dimensional datasets. To fill this gap, a technical framework is proposed in this study to analyze, compare and benchmark the influence of different similarity measures on the results of distance-based clustering algorithms. For reproducibility purposes, fifteen publicly available datasets were used for this study, and consequently, future distance measures can be evaluated and compared with the results of the measures discussed in this work. These datasets were classified as low and high-dimensional categories to study the performance of each measure against each category.
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The Art of Case Study Research - Robert E. Stake - Google Книги

Section 2. This chapter goes further. As illustrated in Figure 2. This has consequences. Many geometry operations in sf , for example, assume their inputs have a projected CRS, because the GEOS functions they are based on assume projected data.
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In medical research , social science , and biology , a cross-sectional study also known as a cross-sectional analysis , transverse study , prevalence study is a type of observational study that analyzes data from a population, or a representative subset, at a specific point in time —that is, cross-sectional data. In economics , cross-sectional studies typically involve the use of cross-sectional regression , in order to sort out the existence and magnitude of causal effects of one independent variable upon a dependent variable of interest at a given point in time. They differ from time series analysis , in which the behavior of one or more economic aggregates is traced through time.
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Spatial analysis or spatial statistics includes any of the formal techniques which studies entities using their topological , geometric , or geographic properties. Spatial analysis includes a variety of techniques, many still in their early development, using different analytic approaches and applied in fields as diverse as astronomy , with its studies of the placement of galaxies in the cosmos , to chip fabrication engineering, with its use of "place and route" algorithms to build complex wiring structures. In a more restricted sense, spatial analysis is the technique applied to structures at the human scale, most notably in the analysis of geographic data. Complex issues arise in spatial analysis, many of which are neither clearly defined nor completely resolved, but form the basis for current research.
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