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- book: ”The Elements of Statistical Learning, Data Mining, Inference, and Prediction” by Trevor Hastie, Robert...
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- deployment (IBM SPSS Data Collection), data mining (IBM SPSS Modeler), text analytics, statistical analysis...
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- tool to assess evolutionary algorithms for data mining problems. This paper introduces a software tool ... tool to assess evolutionary algorithms for Data Mining problems of various kinds including as regression...
- Referenced in 48 articles
- SLIQ: A fast scalable classifier for data mining. Classification is an important problem ... emerging field of data mining. Although classification has been studied extensively in the past, most ... data, thus limiting their suitability for data mining large data sets. This paper discusses issues ... making it an attractive tool for data mining...
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- Sequential pattern mining is an important data mining problem with broad applications. It is challenging...
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- SPRINT: a scalable parallel classifier for data mining. Classification is an important data mining problem ... memory. This limits their suitability for mining over large databases. We present a new decision ... proposed algorithm an ideal tool for data mining...
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- FactoMineR: Multivariate Exploratory Data Analysis and Data Mining with R , an R package for exploratory...
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- analysis, data management, data visualization, and data mining solutions. Techniques include the widest selection...
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- Summary SQL — A fuzzy tool for data mining. The increasing use of computers for transactions ... used for knowledge discovery and data mining. We show how it can be used...
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- allows easy interfacing of alternative data mining and recommendation facilities. PYTHIA-II is an open...
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- Orange: data mining toolbox in Python. Orange is a machine learning and data mining suite ... analysis and component-based assembly of data mining procedures. In the selection and design ... well as for students of data mining...
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- gives rise to the demand for data-mining tools. BioProspector, a C program using ... promoters, and motifs from yeast expression data...
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- effectively and easily conduct KD and data mining experiments within the framework of rough...
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- signal processing, computer vision, and data mining. Traditional NMF solvers include the multiplicative update rule...
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- fast and scalable tool for data mining in massive graphs. Graphs are an increasingly important ... graph. This work presents a data mining tool, called ANF, that can quickly answer ... number of interesting questions on graph-represented data, such as the following. How robust ... repeatedly answer questions about changing data sources. To enable this drill-down, ANF employs...
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- MineBench: A Benchmark Suite for Data Mining Workloads. Data mining constitutes an important class ... data sets, which require increasingly complex data mining algorithms to sift through them to generate ... sizeable performance gap between data mining systems and algorithms. The first step in closing this ... computer architectures can be optimized for data mining applications. In this paper, we present MineBench...
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- Meningitis data mining by cooperatively using GDT-RS and RSBR. This paper describes an application...
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- large datasets is an important data mining problem. Many classification algorithms have been proposed...
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- most popular open source framework for data stream mining, with a very active growing community...
- Referenced in 11 articles
- rattle: Graphical user interface for data mining in R , Rattle (the R Analytic Tool ... based interface to R functionality for data mining. The aim is to provide a simple ... that allows a user to quickly load data from a CSV file (or via ODBC...