Selection of Alternative Projects Using Data Mining

Rippa, Sergey; Lendyuk, Taras

doi:10.1109/idaacs.2007.4488480

Cited by 2 publications

(2 citation statements)

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“…Hoy se encuentran diversas herramientas software para apoyar el desarrollo de proyectos de minería de datos (Britos et al, 2005;Kdnuggets, 2005;MetaGroup, 2004). Basado en el listado de herramientas que aparecen en MetaGroup (2004) y Kdnuggest (2005), se realizó una valoración de las más representativas, entre ellas: Clementine (Khabaza & Shearer, 1995;SPSS-Inc., 2009), Insightful Miner (Insightful-Corporation), WEKA (Holmes, Donkin & Witten, 1994;University-of-Waikato, 2009), CART (Salford-System, 2009), PolyAnalyst (Mai, Krishna & Reddy, 2005;Megaputer, 2009;Rippa & Lendyuk, 2007) y SAS Enterprise Miner (SAS, 2009a). Los criterios generales para dicha valoración fueron: el acceso (costo de las herramientas), la interfaz de usuario (facilidad o dificultad que puede llegar a tener el uso de la herramienta por parte de los usuarios), el proceso (o metodología) en la que se basan, la extensibilidad (capacidad de ampliar fácil y dinámicamente el conjunto de algoritmos que ofrece la herramienta) y el soporte al desarrollo del proyecto por parte de equipos de trabajo.…”

Section: Introductionunclassified

“…A range of software tools are available today that help in carrying out data mining software projects (Britos et al, 2005;Kdnuggets, 2005;MetaGroup, 2004). Based on the list of such tools that appear in MetaGroup (MetaGroup, 2004) and Kdnuggets (Kdnuggets, 2005), an evaluation was made of the most representative, including: Clementine (Khabaza & Shearer, 1995;SPSS-Inc., 2009), Insightful Miner (Insightful-Corporation), WEKA (Holmes, Donkin, & Witten, 1994;University-of-Waikato, 2009), CART (Salford-System, 2009), PolyAnalyst (Mai, Krishna, & Reddy, 2005;Megaputer, 2009;Rippa & Lendyuk, 2007) and SAS Enterprise Miner (SAS, 2009a). The general criteria for such evaluation were: its access (cost of the tools), its user interface (how easy or complex the tool was to use according to the user), the process (or methodology) on which it was based, its extensibility (the capacity to easily and dynamically expand the set of algorithms it offers) and support in project development for individuals to work together in groups.…”

Section: Introductionmentioning

confidence: 99%

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CMIN - a CRISP-DM-based case tool for supporting data mining projects

et al. 2010

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This paper introduces CMIN, an integrated computer aided software engineering (CASE) tool based on cross-industry standard process for data mining (CRISP-DM) 1.0 designed to support carrying out data mining projects. It is “integrated” in the sense that it supports all phases of a process. A general overview of how CMIN works is presented first, including a treatment of processes, templates and project management. CMIN´s capacity for easily and intuitively monitoring projects is highlighted, as is the manner in which CMIN allows a user to increase knowledge regarding using CRISP-DM or any other process defined in the CASE tool through the help and information presented in each step. Next, it is shown how CMIN can bind new data mining algorithms in runtime (without the need to recompile the tool) to support modelling tasks (based on a Workflow) and evaluate data mining projects. Finally, the results of two evaluations of the tool, some conclusions and suggestions for future work are presented.

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Section: Introductionunclassified

Section: Introductionmentioning

confidence: 99%