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Advanced Studies in Classification and Data Science

This edited volume focuses on the latest developments in classification and data science and covers a wide range of topics in the context;

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Model-Based Clustering and Classification for Data Science

, cluster merging, variable selection, semi-supervised and robust classification, clustering of functional data, text and images, and co-clustering;

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Spatial Big Data Science

observation imagery big data. Specifically, the authors introduce several recent spatial classification techniques, such as spatial decision trees and;

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The Data Revolution

Widely acknowledged as being the first academic text to provide a critical overview of the (big) data revolution and the classification;

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The Data Revolution

Widely acknowledged as being the first academic text to provide a critical overview of the (big) data revolution and the classification;

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Mathematical Problems in Data Science

This book describes current problems in data science and Big Data. Key topics are data classification, Graph Cut, the Laplacian Matrix;

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Advanced Hybrid Information Processing

more remaining issues waiting for solving, such as classification and systemization of big data, objective tracking and behavior understanding;

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Advanced Hybrid Information Processing

more remaining issues waiting for solving, such as classification and systemization of big data, objective tracking and behavior understanding;

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Managing and Mining Graph Data

Managing and Mining Graph Data is a comprehensive survey book in graph management and mining. It contains extensive surveys on a variety;

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Managing and Mining Graph Data

Managing and Mining Graph Data is a comprehensive survey book in graph management and mining. It contains extensive surveys on a variety;

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Data Science

This edited volume on the latest advances in data science covers a wide range of topics in the context of data analysis and classification;

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Remotely Sensed Data Characterization, Classification, and Accuracies

A volume in the Remote Sensing Handbook series, Remotely Sensed Data Characterization, Classification, and Accuracies documents the;

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Decomposition Methodology For Knowledge Discovery And Data Mining

importance and necessity. This book provides an introduction to the field with an emphasis on advanced decomposition methods in general data mining;

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Hands-On Data Science with Anaconda

to find solutions for clustering, classification, and linear regression -Analyze your data efficiently with the most powerful data science;

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Learning from Imbalanced Data Sets

problems, and the scalability related to Big Data. Examples of software libraries and modules to address imbalanced classification are provided;

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Learning from Imbalanced Data Sets

problems, and the scalability related to Big Data. Examples of software libraries and modules to address imbalanced classification are provided;

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Data Analysis and Rationality in a Complex World

developments and practical applications related to classification and clustering, data gathering, exploratory and multivariate data analysis;

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Data Complexity in Pattern Recognition

Automatic pattern recognition has uses in science and engineering, social sciences and finance. This book examines data complexity and its;

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Data Complexity in Pattern Recognition

Automatic pattern recognition has uses in science and engineering, social sciences and finance. This book examines data complexity and its;

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Predictive Analytics

Provides a foundation in classical parametric methods of regression and classification essential for pursuing advanced topics in predictive;

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Mastering Spark for Data Science

methods, and popular data science tools, and assumes you have previously run proof of concept studies and built prototypes. What You Will Learn;

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Data Science Concepts and Techniques with Applications

This textbook comprehensively covers both fundamental and advanced topics related to data science. Data science is an umbrella term that;

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Advances in Classification and Data Analysis

This volume contains a selection of papers presented at the biannual meeting of the Classification and Data Analysis Group of Societa;

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Computer Processing Of Remotely-Sensed Images

studies, including full data sets, * Includes new chapter on Remote Sensing and Environmental GIS that provides insights into the ways in which;

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Applying Data Science

real-world case studies, Svolba combines data science and advanced analytics with business questions, illustrating them with data and SAS code;

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Hardware Based Packet Classification for High Speed Internet Routers

Decomposition, and Topological Transformations. * Provides case studies and examples throughout. Hardware Based Packet Classification for High;

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Data Science with Python

Leverage the power of the Python data science libraries and advanced machine learning techniques to analyse large unstructured datasets and;

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