Tabular classification model config

Attributes

The model config YAML file for tabular classification should contain the following attributes:

Attribute	Type	Default	Description	Comments
`architectureType`	str	-	The model's framework.	Must be one of: `sklearn`, `xgboost`, `fasttext`, `keras`, `pytorch`, `rasa`, `tensorflow`, `transformers`, `llm`. If the framework being used is not one of the above, use `custom`.
`categoricalFeatureNames`	List[str]	[]	A list containing the names of all categorical features used by the model.	E.g. ["Gender", "Geography"].
`classNames`	List[str]	-	List of class names corresponding to the outputs of your prediction function.	E.g. ["Retained", "Exited"].
`featureNames`	List[str]	[]	List of input feature names.
`metadata`	Dict[str, any]	{}	Dictionary containing metadata about the model.	This is the metadata that will be displayed on the Openlayer platform.
`name`	str	-	Name of the model.
`predictionThreshold`	float	None	The threshold used to determine the predicted class.	Applies only if you are using a binary classifier and you provided the `predictionScoresColumnName` with the lists of class probabilities in your datasets. If you provided `predictionScoresColumnName` but not `predictionThreshold`, the predicted class is defined by the argmax of the lists in `predictionScoresColumnName`.

Examples

Let’s look at an example dataset from one of the sample notebooks from Openlayer’s examples gallery GitHub repository.

A valid model_config.yaml file would be:

architectureType: sklearn
categoricalFeatureNames:
- Gender
- Geography
classNames:
- Retained
- Exited
featureNames:
- CreditScore
- Geography
- Gender
- Age
- Tenure
- Balance
- NumOfProducts
- HasCrCard
- IsActiveMember
- EstimatedSalary
name: Churn prediction model