From the course: Exploring Data Science with .NET using Polyglot Notebooks & ML.NET

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Training classification models

Training classification models

From the course: Exploring Data Science with .NET using Polyglot Notebooks & ML.NET

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Training classification models

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- [Instructor] In this video, we're going to train a binary classification model to classify whether a specific sales row is associated with a senior salesperson or a non-senior salesperson. Because we're trying to predict if something is one category or the other, that is a classification problem. The classes involved would be is senior sales and non-senior sales. Because there are only two classes, that's a binary classification problem. In order to run a classification experiment in ml.net, we'll need to do a few things. First, we'll need to configure some settings. I already have some binary experiment settings here. Here I'm declaring that the maximum time that I want Auto ML to take is 10 seconds. Auto ML is going to look at a bunch of different options in terms of model trainers and hyper parameters for those model trainers, and in those 10 seconds it's going to see all the options it can evaluate, and it's going to find the best one, and that's going to be the model it…

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