Results 11 to 20 of about 18,376 (197)
System Design to Utilize Domain Expertise for Visual Exploratory Data Analysis
Information, 2021 Exploratory data analysis (EDA) is an iterative process where data scientists interact with data to extract information about their quality and shape as well as derive knowledge and new insights into the related domain of the dataset.
Tristan Langer, Tobias Meisen
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Exploratory Data Analysis of Human Activity Recognition Based on Smart Phone
IEEE Access, 2021 In a smart urban environment, providing accurate information about human activities is an important task. It is a trend to implement human activity recognition (HAR) algorithms and applications on smart phones, including health monitoring, self ...
Weiheng Kong, Lili He, Hailong Wang
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Cybergeo, 2019 Big data is a field of investigation rich in promises but still complex in renewing spatial mobility analysis. In fact, thinking about mobility through the prism of digital footprints raises many questions regarding the data nature, the accessibility ...
Boris Mericskay
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An intelligent assistant for exploratory data analysis [PDF]
, 1997 In this paper we present an account of the main features of SNOUT, an intelligent assistant for exploratory data analysis (EDA) of social science survey data that incorporates a range of data mining techniques.
B. S. Everitt +17 more
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A propos de l’analyse spatiale exploratoire des données
Cybergeo, 2001 Since the geographical information system revolution of the mid-1980s, there has been a rapid growth in the number of spatially referenced databases.
Arnaud Banos
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Exploratory data analysis in the context of data mining and resampling.
International Journal of Psychological Research, 2010 Today there are quite a few widespread misconceptions of exploratory data analysis (EDA). One of these misperceptions is that EDA is said to be opposed to statistical modeling.
Chong Ho Yu
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Exploratory Analysis of Benchmark Experiments -- An Interactive Approach [PDF]
, 2009 The analysis of benchmark experiments consists in a large part of exploratory methods, especially visualizations. In Eugster et al. [2008] we presented a comprehensive toolbox including the bench plot.
Eugster, Manuel J. A., Leisch, Friedrich
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Current exploratory and confirmatory issues in data analysis in psychology
International Journal of Psychological Research, 2010 In 1968 John Tukey gave a speech at the American Psychological Association in San Francisco about the relevance of proper data analysis in Psychology (Tukey, 1969). His closing message was that “data analysis needs to be both exploratory and confirmatory”
Fernando Marmolejo-Ramos
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Towards High-Performance Exploratory Data Analysis (EDA) via Stable Equilibrium Point
, 2023 Exploratory data analysis (EDA) is a vital procedure for data science projects. In this work, we introduce a stable equilibrium point (SEP) - based framework for improving the efficiency and solution quality of EDA. By exploiting the SEPs to be the representative points, our approach aims to generate high-quality clustering and data visualization for ...
Yuxuan Song, Yongyu Wang
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A randomized trial in a massive online open course shows people don't know what a statistically significant relationship looks like, but they can learn [PDF]
, 2014 Scatterplots are the most common way for statisticians, scientists, and the public to visually detect relationships between measured variables. At the same time, and despite widely publicized controversy, P-values remain the most commonly used measure to
Anderson, G. Brooke +3 more
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