This manuscript provides an in-depth analysis of Major League Baseball (MLB) team performance from 2005 to 2023 using datavisualization in Tableau and proposed an hybrid datavisualization model (VisMLB) for Major Le...
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This manuscript provides an in-depth analysis of Major League Baseball (MLB) team performance from 2005 to 2023 using datavisualization in Tableau and proposed an hybrid datavisualization model (VisMLB) for Major Le...
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ISBN:
(数字)9798331533205
ISBN:
(纸本)9798331533212
This manuscript provides an in-depth analysis of Major League Baseball (MLB) team performance from 2005 to 2023 using datavisualization in Tableau and proposed an hybrid datavisualization model (VisMLB) for Major League Baseball matches. The objective is to identify key metrics, such as batting, fielding, and pitching, that influence team success, including championship wins. The authors analyze the total number of championships won by each team, compare top-performing teams based on a variety of performance metrics, and explore the relationship between On-Base Percentage (OBP) and Slugging Percentage (SLG) for home and visitor teams in relation to home victories. Using Tableau, feature importance is visualized, and predictive models are evaluated for accuracy, precision, and recall. The findings offer a comprehensive overview of MLB performance trends over nearly two decades.
Although there are a number of visualization systems to choose from when analyzing data, only a few of these allow for the integration of other visualization and analysis techniques. There are even fewer visualization...
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ISBN:
(纸本)081945642X
Although there are a number of visualization systems to choose from when analyzing data, only a few of these allow for the integration of other visualization and analysis techniques. There are even fewer visualization toolkits and frameworks from which one can develop ones own visualization applications. Even within the research community, scientists either use what they can from the available tools or start from scratch to define a program in which they are able to develop new or modified visualization techniques and analysis algorithms. Presented here is a new general-purpose platform for constructing numerous visualization and analysis applications. The focus of this system is the design and experimentation of new techniques, and where the sharing of and integration with other tools becomes second nature. Moreover, this platform supports multiple large data sets, and the recording and visualizing of user sessions. Here we introduce the Universal visualization Platform (UVP) as a modern datavisualization and analysis system.
We present an application case study for visualizing large data sets of time series spatial data. Our application is built on a flexible, object oriented framework that supports the visualization of dynamic internal w...
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ISBN:
(纸本)081945642X
We present an application case study for visualizing large data sets of time series spatial data. Our application is built on a flexible, object oriented framework that supports the visualization of dynamic internal wave propagation in the earth's tropopause. Our data model uses a multiresolution hierarchy that integrates spatial and temporal components. The data also includes error information at each level of the hierarchy. The application provides the scientist with tools necessary to examine, query, and interact with visualizations of data of interest.
Scientific visualization is routinely promoted as an indispensable component of the knowledge discovery process in a variety of scientific and engineering disciplines. However, our experiences with visualization at th...
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ISBN:
(纸本)081945642X
Scientific visualization is routinely promoted as an indispensable component of the knowledge discovery process in a variety of scientific and engineering disciplines. However, our experiences with visualization at the National Center for Atmospheric Research (NCAR) differ somewhat from those described by many in the visualization community. visualization at NCAR is used with great success to convey highly complex results to a wide variety of audiences, but the technology only rarely plays an active role in the day-to-day scientific discovery process. We believe that one reason for this is the mismatch between the size of the primary simulation data sets produced and the capabilities of the software and visual computing facilities generally available for their analysis. Here we describe preliminary results of our efforts to facilitate visual as well as non-visual analysis of terascale scientific data sets with the aim of realizing greater scientific return from such large scale computation efforts.
The reorderable matrix method is a convenient way of representing static tabular data (i.e. matrices) visually. In this paper, we present an approach to use the reorderable matrix method for visualizing time-varying m...
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ISBN:
(纸本)081945642X
The reorderable matrix method is a convenient way of representing static tabular data (i.e. matrices) visually. In this paper, we present an approach to use the reorderable matrix method for visualizing time-varying matrix data. Solutions to the problems encountered during the adaptation of this visualization method for time-varying matrices and proposals to solve the problems related to the automatic reordering of static tabular data are discussed. The approach is illustrated by visualizing sensitivity matrices generated during the simulation of metabolic network models.
In this paper, we try to provide a global view of DNA microarray gene expression dataanalysis and modeling process by combining novel and effective visualization techniques with data mining algorithms. An integrated ...
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ISBN:
(纸本)081945642X
In this paper, we try to provide a global view of DNA microarray gene expression dataanalysis and modeling process by combining novel and effective visualization techniques with data mining algorithms. An integrated framework has been proposed to model and visualize short, high-dimensional gene expression data. The framework reduces the dimensionality of variables before applying appropriate temporal modeling method. Prototype has been built using Java3D to visualize the framework. The prototype takes gene expression data as input, clusters the genes, displays the clustering results using a novel graph layout algorithm, models individual gene clusters using Dynamic Bayesian Network and then visualizes the modeling results using simple but effective visualization techniques.
Cutting-edge biological and bioinformatics research seeks a systems perspective through the analysis of multiple types of high-throughput and other experimental data for the same sample. Systems-level analysis require...
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ISBN:
(纸本)0769523447
Cutting-edge biological and bioinformatics research seeks a systems perspective through the analysis of multiple types of high-throughput and other experimental data for the same sample. Systems-level analysis requires the integration and fusion of such data, typically through advanced statistics and mathematics. visualization is a complementary computational approach that supports integration and analysis of complex data or its derivatives. We present a bioinformatics visualization prototype, Juxter, which depicts categorical information derived from or assigned to these diverse data for the purpose of comparing patterns across categorizations. The visualization allows users to easily, discern correlated and anomalous patterns in the data. These patterns, which might not be detected automatically by, algorithms, may, reveal valuable information leading to insight and discovery. We describe the visualization and interaction capabilities and demonstrate its utility in a new field, metagenomics, which combines molecular biology and genetics to identify and characterize genetic material from multi-species microbial samples.
Visual simulation can be efficiently performed using programmable graphics hardware. However, in utilizing hardware to maximize throughput, it is important not to constrain interactivity. We present a method of using ...
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ISBN:
(纸本)081945642X
Visual simulation can be efficiently performed using programmable graphics hardware. However, in utilizing hardware to maximize throughput, it is important not to constrain interactivity. We present a method of using the graphics hardware while maintaining full interactivity during simulation exploration. This interactivity involves: temporal exploration, data probing and modification, simulation model modification, and user defined visual metadata. Results are shown using our application for exploring a reaction-diffusion simulation.
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