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Classification, Clustering, and Data Analysis: Recent Advances and Applications (Studies in Classification, Data Analysis, and Knowledge Organization)

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Data Analysis, Classification, and Related Methods (Studies in Classification, Data Analysis, and Knowledge Organization)

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Springer - Data Analysis and Classification Book

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Advances in Data Science and Classification: Proceedings of the 6th Conference of the International Federation of Classification Societies (IFCS-98) ... Data Analysis, and Knowledge Organization)

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Data Without Labels: Practical Unsupervised Machine Learning

Model-Based Clustering and Classification for Data Science: With Applications in R: Series Number 50 (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 50)

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New Perspectives in Statistical Modeling and Data Analysis: Proceedings of the 7th Conference of the Classification and Data Analysis Group of the ... Data Analysis, and Knowledge Organization)

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Data Clustering in C++: An Object-Oriented Approach: 20 (Chapman & Hall/CRC Data Mining and Knowledge Discovery)

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Statistical Learning and Data Science (Chapman & Hall/CRC Computer Science & Data Analysis)

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Statistical Learning and Data Science (Computer Science and Data Analysis)

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Social Media Analytics for User Behavior Modeling: A Task Heterogeneity Perspective (Data-Enabled Engineering)

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Data Clustering with Python: From Theory to Implementation (Chapman & Hall/CRC The Python Series)

Recent Advances in Hybrid Metaheuristics for Data Clustering (The Wiley Series in Intelligent Signal and Data Processing)

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Advanced Methods in Statistics, Data Science and Related Applications: SIS 2022, Caserta, Italy, June 22–24: 467 (Springer Proceedings in Mathematics & Statistics, 467)

Recent Advances in Information and Communication Technology 2018: Proceedings of the 14th International Conference on Computing and Information ... in Intelligent Systems and Computing, 769)

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Model-Based Clustering, Classification, and Density Estimation Using mclust in R (Chapman & Hall/CRC The R Series)

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Granular Computing Based Machine Learning: A Big Data Processing Approach: 35 (Studies in Big Data, 35)

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Feature Selection for Data and Pattern Recognition: 584 (Studies in Computational Intelligence, 584)

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