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A Framework for Modeling Critical Success Factors in the Selection of Machine Learning Algorithms for Breast Cancer Recognition
Conference ObjectAbstract: Analysis of critical success factors allows software development organizations to focus on the factoPalabras claves:Bosom cancer recognition, Critical success factors, Fuzzy Mental Maps, Machine learningAutores:Eddy Raul Montenegro Marin, Galo Valverde Landivar, Maikel Yelandi Leyva Vazquez, Miguel Ángel Quiroz MartínezFuentes:scopusA Framework for Selecting Machine Learning Models Using TOPSIS
Conference ObjectAbstract: In machine learning, it is common when multiple algorithms are applied to different data sets that aPalabras claves:Breast Cancer, Breast cancer Wisconsin dataset, Data set, Machine learning, TOPSISAutores:Luis Andy Briones Peñafiel, Maikel Yelandi Leyva Vazquez, Miguel Ángel Quiroz Martínez, Steven Xavier Sanchez MuñozFuentes:scopusA Machine Learning Model Comparison and Selection Framework for Software Defect Pbkp_rediction Using VIKOR
Conference ObjectAbstract: In today’s time, software quality assurance is the most essential and costly set of activities durinPalabras claves:Machine learning, MCDM, NASA dataset, Software defect pbkp_rediction, VIKOR methodAutores:Byron Alcívar Martínez Tayupanda, Luis Andy Briones Peñafiel, Miguel Ángel Quiroz Martínez, Sulay Stephanie Camatón PaguayFuentes:googlescopusA framework for selecting classification models in the intruder detection system using topsis
Conference ObjectAbstract: As the network has expanded considerably, security mechanisms are a key issue in networks. IntrusivePalabras claves:INTRUSION DETECTION SYSTEM (IDS), Machine learning, NSL-KDD, TOPSISAutores:Carlos Jose Espinoza Alcivar, Deivid Temistocles Leon Rugel, Maikel Yelandi Leyva Vazquez, Miguel Ángel Quiroz MartínezFuentes:googlescopusDeep Learning for Edge Computing: A Survey
Conference ObjectAbstract: A compendium of Deep Learning algorithms that are applied in Edge Computing through IoT devices thatPalabras claves:Data Analysis, deep learning, Edge computing, Machine learning, SurveyAutores:Cordero Solis L.B., Galo Valverde Landivar, Joffre Luis Leon Veas, Miguel Ángel Quiroz MartínezFuentes:scopusAn Analysis of Deep Learning Architectures for Cancer Diagnosis
Conference ObjectAbstract: It was analyzed the reference information on Deep Learning applications in the areas of diagnosis anPalabras claves:architectures, Cancer diagnosis, deep learning, Machine learningAutores:Bedor Caballero J.A., Daniel Humberto Plua Moran, Galo Valverde Landivar, Maikel Yelandi Leyva Vazquez, Miguel Ángel Quiroz MartínezFuentes:googlescopusAn Efficient Approach for Selecting QoS-Based Web Service Machine Learning Models Using Topsis
Conference ObjectAbstract: With the advancement of Service Oriented Architecture (SOA), web services have gained great populariPalabras claves:Machine learning, qos, QWS dataset, TOPSIS, WEB SERVICESAutores:Erick David Alvarado Castillo, Josue Leonardo Moncayo Redin, Luis Andy Briones Peñafiel, Miguel Ángel Quiroz MartínezFuentes:googlescopusMachine Learning Algorithm Selection for a Clinical Decision Support System Based on a Multicriteria Method
Conference ObjectAbstract: On the current information in the medical area related to cancer analysis, the selection of an optimPalabras claves:Decision clinical, Machine learning, Medical data, multicriteria method, Support aystemAutores:Galo Valverde Landivar, Jonathan Andrés España Arambulo, Maikel Yelandi Leyva Vazquez, Miguel Ángel Quiroz MartínezFuentes:scopus