## Transactions on Rough Sets XVIIThe LNCS journal Transactions on Rough Sets is devoted to the entire spectrum of rough sets related issues, from logical and mathematical foundations, through all aspects of rough set theory and its applications, such as data mining, knowledge discovery and intelligent information processing, to relations between rough sets and other approaches to uncertainty, vagueness, and incompleteness, such as fuzzy sets and theory of evidence. Volume XVII is a continuation of a number of research streams which have grown out of the seminal work by Zdzislaw Pawlak during the first decade of the 21st century. The research streams represented in the papers cover both theory and applications of rough, fuzzy and near sets as well as their combinations. |

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### Contents

1 | |

Standard Errors of Indices in Rough Set Data Analysis | 33 |

A DescriptionBased System
for Quantifying the Nearness or Apartness
of Visual Rough Sets
| 48 |

Rough Sets and Matroids | 74 |

An Efficient Approach for Fuzzy Decision Reduct Computation | 82 |

Rough Sets in Economy and Finance | 109 |

Algorithms for Similarity Relation Learning from High Dimensional Data | 174 |

Author Index | 293 |

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### Common terms and phrases

analysis applications approximation space assessment Boolean classical rough set clustering computation concept conditional attributes conditional variables considered construction context data sample data set decision attribute decision classes decision reduct decision rules decision system defined Definition described description-based descriptive discretization DRBS equivalence relation evaluation example expert feature selection financial ratios forecasting fuzzy rough set fuzzy sets genetic algorithms given Heidelberg implication IMQRA IMQRA_MW information system input LNCS lower approximation Lukasiewicz Machine Learning matroid measure methods modal logic MQRA neural network pair parameters Pawlak positive region prediction probe functions problem properties proposed Proximity System Random Forest RBS model rough set approach rough set based rough set model rough set theory Rule-Based Similarity semantic SIM(u similarity function similarity matrices similarity models similarity relation Skowron Springer support vector machines t-norm Table three-valued logics upper approximation values vector visual rough sets