So the first subject that we’re going to be discussing in this course is regression. And particularly, in this lecture, we will be discussing something called linear regression.
So this is the most basic form of regression. And to introduce it, I’ll use a very simple problem, the problem of Old Faithful. So with this problem, what we have is a geyser that’s erupting for a certain amount of time. And then not erupting for a certain amount of time.
And what we want to do is we want to come up with a way to predict when is the next eruption going to be. And so one way that we might do this is to collect some data. So collect pairs of inputs and outputs. Where the input might be how long the geyser erupted for in minutes. And then the output would be after that eruption, how long we had to wait for the next eruption in minutes.
Artículo completo: https://dademuchconnection.wordpress.com/2017/08/05/machine-learning-regression/
Written by: Larry Francis Obando – Technical Specialist
Escuela de Ingeniería Eléctrica de la Universidad Central de Venezuela, Caracas.
Escuela de Ingeniería Electrónica de la Universidad Simón Bolívar, Valle de Sartenejas.
Escuela de Turismo de la Universidad Simón Bolívar, Núcleo Litoral.
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