About supervised machine learning, in the context of Linear Regression; Decision tree; Logistics Regresion; Randon forest and neural network, which metrics should be used to know if a classification model is good and why use them? What about regression, what metrics are used to say how good the model is? What is the best for each case?
About supervised machine learning, in the context of Linear Regression; Decision tree; Logistics Regresion; Randon forest and neural network, which metrics should be used to know if a classification model is good and why use them? What about regression, what metrics are used to say how good the model is? What is the best for each case?
Elements Of Electromagnetics
7th Edition
ISBN:9780190698614
Author:Sadiku, Matthew N. O.
Publisher:Sadiku, Matthew N. O.
ChapterMA: Math Assessment
Section: Chapter Questions
Problem 1.1MA
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About supervised machine learning, in the context of Linear Regression; Decision tree; Logistics Regresion; Randon forest and neural network, which metrics should be used to know if a classification model is good and why use them? What about regression, what metrics are used to say how good the model is? What is the best for each case?
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