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El modelo de CRISP-DM es flexible y se pueden personalizar fácilmente. Por ejemplo, si su organización intenta detectar actividades de blanqueo de dinero, es probable que necesite realizar una criba de grandes cantidades de datos sin un objetivo de modelado específico.
1 de ene. de 2021 · The main findings are that CRISP-DM is still a de-factor standard in data mining, but there are challenges since the most studies do not foresee a deployment phase. The contribution of our paper is to identify best practices and process phases in which data mining analysts can be better supported.
12 de mar. de 2023 · What is Deployment in CRISP-DM? The Deployment phase of the CRISP-DM methodology refers to the process of taking the solutions generated in the modeling phase and putting them into action.
18 de ene. de 2021 · What is CRISP-DM? At some point working in data science, it is common to come across CRISP-DM. I like to irreverently call it the Crispy Process. It is an old concept for data science that’s been around since the mid-1990s. This post is meant as a practical guide to CRISP-DM.
Capítulo 1. Introducción al CRISP-DM....................................................................1. Conceptos básicos de ayuda de CRISP-DM................................................................................................1.
28 de abr. de 2024 · The CRoss Industry Standard Process for Data Mining (CRISP-DM) is a process model with six phases that describes the data science life cycle.
30 de oct. de 2023 · CRISP-DM is a widely used framework for data mining that outlines a structured approach to planning, executing, and evaluating data mining projects. It provides a step-by-step process that...
