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Required Feature Group Types

To train a model under this use case, you will need to create feature groups of the following type(s):

Feature Group Type	API Configuration Name	Required	Description
Sales Leads Data	TABLE	True	This dataset corresponds to various attributes of the user (e.g., occupation, gender, marital status, etc.) that are relevant to deciding if the user might be a potential customer.

Note: Once you upload the datasets under each Feature Group Type that comply with their respective required schemas, you will need to create Machine learning (ML) features that would be used to train your ML model(s). We use the term, "Feature Group" for a group of ML features (dataset columns) under a specific Feature Group Type. Our system support extensible schemas that enables you to provide any number of additional columns/features that you think are relevant to that Feature Group Type.

Feature Group: Sales Leads Data

This dataset corresponds to various attributes of the user (e.g., occupation, gender, marital status, etc.) that are relevant to deciding if the user might be a potential customer.

Feature Mapping	Feature Type	Required	Description
LEAD_ID	categorical	Y	This is a unique identifier of each user in the user base.
LEAD_SCORE		Y	This denotes if the user turned into a lead (customer) or not. The score can be 0 or 1, 0 for not a customer yet and 1 for a customer
[ATTRIBUTE ABOUT THE LEAD]		Y	Any relevant attribute/variable that can influence the target variable (LEAD_SCORE). The more the number of relevant attributes and the data on them, the better the AI model.