3) Creating a Logistic Regression model in H2O (GLM)

This Blog entry is from the Deep Learning section in Learn R.

With the data loaded, a model now needs to be trained.  Navigate to Models to see the available algorithms:

Models

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In this case, the algorithm is Generalised Linear Modelling (this is Logistic Regression).  Click this model to create the cell in flow:

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There are a multitude of parameters that are quite outside the scope of this document, for the purposes of this document, simply specify the Training and Validation Hex sets:

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Thereafter, specify the dependent variable, known as the Response Column in H2O:

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In this case the Dependent Variable is titled as the same:

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Scroll to the base of the cell and click Build Model to initiate the training process:

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The training process will begin with progress being written out to a newly created job cell:

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At this stage a Logistic Regression model has been created. It is a good idea to save the flow by navigating:

Flow >>> Save Flow

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