III. LA DEFINICIÓN SUBJETIVA DEL VALOR COMO PRINCIPIO PSEUDOCIENTÍFICO (BORRADOR)

ISADORE NABI

Este, y otros capítulos antes subidos, pertenecen a un libro en proceso de construcción titulado “EL SISTEMA DIALÉCTICO-MATERIALISTA COMO PROGRAMA DE DEMARCACIÓN DE LAS CIENCIAS. CASO DE APLICACIÓN: LA DEFINICIÓN SUBJETIVA DEL VALOR DE LAS MERCANCÍAS COMO PRINCIPIO PSEUDOCIENTÍFICO“.

La imagen del encabezado fue tomada de http://davidharvey.org/2018/03/marxs-refusal-of-the-labour-theory-of-value-by-david-harvey/.

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ENCUESTA NACIONAL SOBRE LOS ASPECTOS DE LA VIRTUALIDAD VINCULADOS CON LA PANDEMIA DEL COVID-19 (ENAVIRPA 2021)

ISADORE NABI

VII. REFERENCIAS

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GENERALIDADES DE LA TEORÍA DEL APRENDIZAJE ESTADÍSTICO

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VI. Referencias

Barrios, J. (19 de Julio de 2019). La matriz de confusión y sus métricas . Obtenido de Health BIG DATA: https://www.juanbarrios.com/la-matriz-de-confusion-y-sus-metricas/

Google Developers. (19 de Julio de 2021). Clasificación: Exactitud. Obtenido de https://developers.google.com/machine-learning/crash-course/classification/accuracy

Hastie, T., Tibshirani, R., & Friedman, J. (2017). The Elements of Statistical Learning. Data Mining, Inference, and Prediction (Segunda ed.). New York: Springer.

James, G., Witten, D., Hastie, T., & Tibshirani, R. (2013). An Introduction to Statistical Learning with Applications in R. New York: Springer.

StackExchange Data Science. (19 de Junio de 2016). Is GLM a statistical or machine learning model? Obtenido de https://datascience.stackexchange.com/questions/488/is-glm-a-statistical-or-machine-learning-model

StackOverFlow. (15 de Marzo de 2014). Supervised Learning, Unsupervised Learning, Regression. Obtenido de https://stackoverflow.com/questions/22419136/supervised-learning-unsupervised-learning-regression

Wikipedia. (10 de Julio de 2021). Precision and recall. Obtenido de Bioinformatics: https://en.wikipedia.org/wiki/Precision_and_recall