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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 Angel Quiroz MartinezFuentes: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 Angel Quiroz Martinez, Steven Xavier Sanchez MuñozFuentes:scopusA Machine Learning Model Comparison and Selection Framework for Software Defect Prediction 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 Angel Quiroz Martinez, Sulay Stephanie Camatón PaguayFuentes:googlescopusA New Model for the Selection of Information Technology Project in a Neutrosophic Environment
ArticleAbstract: Usually, companies confront the difficulty to make the best decision about the way to invest their rPalabras claves:Balanced Scorecard Model, Information Technology Project, Neutrosophic Analytic Hierarchy Process, Zero-one linear programmingAutores:González-Caballero E., Jesús Rafael Hechavarría Hernández, Maikel Yelandi Leyva Vazquez, Miguel Angel Quiroz Martinez, Portilla-Castell Y.Fuentes: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 Angel Quiroz MartinezFuentes:googlescopusChatbot for Technical Support, Analysis of Critical Success Factors Using Fuzzy Cognitive Maps
Conference ObjectAbstract: Remote assistance needs to be automated for better coverage in time, quality, and quantity of clientPalabras claves:Chatbots, Critical success factors, Fuzzy cognitive maps simulation, Natural Language, technical supportAutores:Daniel Humberto Plua Moran, Maikel Yelandi Leyva Vazquez, Mayorga Plua S.E., Miguel Angel Quiroz Martinez, Monica Daniela Gomez Rios, Monica Gómez RíosFuentes:googlescopusBenchmarking Neural Networks Activation Functions for Cancer Detection
Conference ObjectAbstract: The choice of the most suitable activation functions for artificial neural networks significantly afPalabras claves:Activation functions, Benchmarking, Cancer detection, Neural networksAutores:Daniel Humberto Plua Moran, Josue Ricardo Borja Vernaza, Maikel Yelandi Leyva Vazquez, Miguel Angel Quiroz MartinezFuentes:googlescopusAnálisis comparativo de algoritmos de detección de objetos con Sensor Láser Lidar 3D
OtherAbstract: La tecnología LiDAR cada vez está teniendo un avance progresivo constante en el campo automotriz enPalabras claves:Autores:Andrea Valentina Cárdenas García, Angel Eduardo Cevallos Villacís, Miguel Angel Quiroz MartinezFuentes:googlerraaeCausal models as an aid to understanding complex systems: Analysis of critical success factors in the development of chatbots
ArticleAbstract: We analyzed the factors that are considered key when developing chatbots, making the implementationPalabras claves:causality, Chatbots, covid-19, Critical success factors, Fuzzy Cognitive MapsAutores:Gruezo J.M., Joseline Mora, Maikel Yelandi Leyva Vazquez, Miguel Angel Quiroz MartinezFuentes: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 Angel Quiroz MartinezFuentes:googlescopus