Knowledge Discovery in Databases: PKDD 2005, 9th European Conference on Principles and Practice of Knowledge Discovery in Databases, Porto, Portugal, October 3-7, 2005, Proceedings
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Machine Learning: ECML 2005, 16th European Conference on Machine Learning, Porto, Portugal, October 3-7, 2005, Proceedings
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متن کامل’ introduction : special issue of the
This special issue is a collection of papers that were submitted to the ECML/PKDD 2014 journal track and have been accepted for publication in “DataMining andKnowledge Discovery”. The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML/PKDD, launched its journal track last year in 2013. In order to cover the full scope of the conference,...
متن کاملData Mining: An AI Perspective
DaWaK 2003: 5th International Conference on Data Warehousing and Knowledge Discovery (September 35, 2003, Prague, Czech Repblic) Abstract--Data mining, or knowledge discovery in databases (KDD), is an interdisciplinary area that integrates techniques from several fields including machine learning, statistics, and database systems, for the analysis of large volumes of data. This paper reviews th...
متن کامل’ s Introduction : Special Issue of the ECML PKDD 2013 Journal Track
The 2013 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECMLPKDD) was held in Prague, September 2013. Following the long-standing tradition of the series, it brought together researchers in Machine Learning and Data Mining for an exciting program of cutting-edge research results, aiming in particular at a cross-fertilization between thes...
متن کاملSong, H., & Flach, P. (2015). Model Reuse with Subgroup Discovery. In Proceedings of the ECML/PKDD 2015 Discovery Challenges: co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2015) (CEUR
In this paper we describe a method to reuse models with Model-Based Subgroup Discovery (MBSD), which is a extension of the Subgroup Discovery scheme. The task is to predict the number of bikes at a new rental station 3 hours in advance. Instead of training new models with the limited data from these new stations, our approach first selects a number of pre-trained models from old rental stations...
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ورودعنوان ژورنال:
دوره 3721 شماره
صفحات -
تاریخ انتشار 2005