Predict with an Existing Model

After you've built a model that fits your needs (such as accuracy or confidence requirements), you can use Predict or Predict Time Series to run that model on different versions of the dataset you used – to generate predictions.

For example, you might get a file in the same format in which you ran Train but without a Z column. You could then use your model to predict the value of the Z column and take action based on those predictions.

To use the Predict form, select ML > Predict in the sidebar. The Predict form appears.

1. Select the model to use.
2. Select either "dataset" for the entire dataset, or "test split" if a test split was used to train the chosen model.
3. Click Submit.

To use the GEL input field, enter: Predict using the model <model> on the dataset <dataset> (considering the test split)

Review Predictions

An easy way to compare your model's performance is to create a confusion matrix with the Chart Builder A confusion matrix is a chart that compares the values of a known column (such as Survived) with the values predicted by your model. The values in each section range from 0 to 1. The closer the number is to 1, the more better the model is at correctly predicting that value.

note

If your target column has 10 or fewer unique values, you'll be prompted to create a matrix after using Predict.

In some cases, you already know the layout of your data in the database and need to work with only a small number of tables inside DataChat. In these cases, you can create a file that contains the queries that you need and, in conjunction with the Load skill, pull only the data you need into DataChat.