Image classification is used to identify images of different categories. Value prediction, which falls under the regression task, is used to predict numbers. Data classificationĬlassification is used to categorize data into categories. The type of scenario depends on what type of prediction you are trying to make. In Model Builder, you need to select a scenario. Which machine learning scenario is right for me? route customer feedback issues to the correct team in your companyĮach scenario maps to a different Machine Learning Task which include:įor example, the scenario of classifying sentiments as positive or negative would fall under the binary classification task.įor more information about the different ML Tasks supported by ML.NET see Machine learning tasks in ML.NET.detect whether a banking transaction is fraudulent.classify sentiments as positive or negative based on customer reviews.predict future product sales volume based on historical sales data.You can bring many different scenarios to Model Builder, to generate a machine learning model for your application.Ī scenario is a description of the type of prediction you want to make using your data. This name is applied to the consumption, training, and model files. When you create your mbconfig file, you're prompted for a name.
NUKE MODEL BUILDER ZIP FILE
Model.zip: This is a serialized zip file which represents your trained ML.NET model.You can use this pipeline for re-training your model.
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: This file contains the ModelInput and ModelOutput schemas as well as the Predict function generated for consuming the model.The mbconfig file keeps track of everything you do in Model Builder to allow you to reopen the session.Īfter training, three files are generated under the *.mbconfig file: This will create an mbconfig configuration file inside of the project. When you first start up Model Builder it will ask for you to name the project.