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A Rank-by-Feature Framework for Unsupervised Multidimensional Data Exploration Using Low Dimensional Projections
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Feature Selection for Knowledge Discovery and Data Mining
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Interactively Exploring Hierarchical Clustering Results
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Coordinating Computational and Visual Approaches for Interactive Feature Selection and Multivariate Clustering
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Exploratory Projection Pursuit
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Similarity clustering of dimensions for an enhanced visualization of multidimensional data
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Interactive hierarchical dimension ordering, spacing and filtering for exploration of high dimensional datasets
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Parallel coordinates: a tool for visualizing multi-dimensional geometry
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XmdvTool: integrating multiple methods for visualizing multivariate data
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The Grand Tour: A Tool for Viewing Multidimensional Data
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Automatic subspace clustering of high dimensional data for data mining applications
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Fast algorithms for projected clustering
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Introduction to the Practice of Statistics
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Projection Pursuit Indexes Based on Orthonormal Function Expansions
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Incoming claims: where this work appears in other papers’ reference lists and arguments.
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