A category classification model is a model that learns with labeled learning data first, and then predicts which class the newly entered data belongs to. The classification falls under the Map Learning category, where the target comes with the input data. There are many applications for classification in many areas such as credit approval, medical diagnosis, and target marketing.

1. Creating the New Verification Project

If new data is utilized, upload the data from the dataset. (For more information, see Dataset > Upload Data.)

  1. Click a Dataset from the top menu, or click Verifying from the top menu and click the New Project button on the center-left side of the screen.

  2. Check to the left of the dataset to be used for training and click the Start AI Verification button.

2. Setting Up the Model Training Options for Verification

  1. Sets the Training Method to Structured Data Automatic Classification or Structured Data Category Classification.

  2. Sets the Preferred Method.

  3. Set other options for model training. (For more information, see Verifying > Training the Model for Verification > Model Training Options for Verification.)

3. Setting Up a Dataset for Verification

  1. Check whether learning is enabled by the data's properties(columns) and disable training data if there are properties to exclude.

  2. If data preprocessing is required by the data's properties(column), mark the preprocessing check box for the properties and click the Preprocessing button at the top of the data information table.

4. Starting Model Training for Verification

  1. Click the START button on the right to start training the model with the options setted up.

  2. E-mail and notification will be sent when the initial model training is complete, and e-mail and notification will be sent once more when all models in the project have completed training.

Do you have any other questions? [email protected]

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