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Core concepts in data analysis: summarization, correlation and visualization

✍ Scribed by Mirkin, Boris Grigorʹevich

Publisher
Springer
Year
2011
Tongue
English
Leaves
402
Series
Undergraduate topics in computer science
Category
Library
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✦ Table of Contents

Introduction.-1D Analysis: Summarization and Visualisation of a Single Feature.-2D Analysis: Correlation and Visualition of Two Features.-Learning Multivariate Correlations in Data.-Principal Component Analysis and SVD.-K-Means and Related Clustering Methods.-Hierarchial Clustering.-Approximate and Spectral Clustering for Network and Affinity Data.

✦ Subjects

artificial intelligence;computer sciences;computerwetenschappen;Informatie- en communicatietechnologie (algemeen);Information and Communication Technology (General);Informatique;kunstmatige intelligentie;mathematics;patroonherkenning;pattern recognition;probability;statistics;statistiek;waarschijnlijkheid;wiskunde;Mathematical statistics--Data processing;Data mining;Electronic books;Mathematical statistics -- Data processing

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Core Concepts in Data Analysis: Summariz
πŸ“ Core Concepts in Data Analysis: Summarization, Correlation and Visualization
✍ Boris Mirkin (auth.) πŸ“‚ Library πŸ“… 2011 πŸ› Springer-Verlag London 🌐 English

<p><p><i>Core Concepts in Data Analysis: Summarization, Correlation and Visualization</i><b></b>provides in-depth descriptions of those data analysis approaches that either summarize data (principal component analysis and clustering, including hierarchical and network clustering) or correlate differ

Core Concepts in Data Analysis: Summariz
πŸ“ Core Concepts in Data Analysis: Summarization, Correlation and Visualization
✍ Boris Mirkin (auth.) πŸ“‚ Library πŸ“… 2011 πŸ› Springer-Verlag London 🌐 English

<p><p><i>Core Concepts in Data Analysis: Summarization, Correlation and Visualization</i><b></b>provides in-depth descriptions of those data analysis approaches that either summarize data (principal component analysis and clustering, including hierarchical and network clustering) or correlate differ

Core Concepts in Data Analysis: Summariz
πŸ“ Core Concepts in Data Analysis: Summarization, Correlation and Visualization
✍ Mirkin, Boris πŸ“‚ Library πŸ“… 2011 πŸ› Springer London : Imprint : Springer 🌐 English

Core Concepts in Data Analysis: Summarization, Correlation and Visualization provides in-depth descriptions of those data analysis approaches that either summarize data (principal component analysis and clustering, including hierarchical and network clustering) or correlate different aspects of data

Core Concepts in Data Analysis: Summariz
πŸ“ Core Concepts in Data Analysis: Summarization, Correlation and Visualization
✍ Boris Mirkin (auth.) πŸ“‚ Library πŸ“… 2011 πŸ› Springer-Verlag London 🌐 English

<p><p><i>Core Concepts in Data Analysis: Summarization, Correlation and Visualization</i><b></b>provides in-depth descriptions of those data analysis approaches that either summarize data (principal component analysis and clustering, including hierarchical and network clustering) or correlate differ

Core Data Analysis: Summarization, Corre
πŸ“ Core Data Analysis: Summarization, Correlation, and Visualization
✍ Boris Mirkin πŸ“‚ Library πŸ“… 2019 πŸ› Springer International Publishing 🌐 English

<p><p>This text examines the goals of data analysis with respect to enhancing knowledge, and identifies data summarization and correlation analysis as the core issues. Data summarization, both quantitative and categorical, is treated within the encoder-decoder paradigm bringing forward a number of m