Task Types

Predictive queries can address a variety of predictive problems. The task type is determined by the structure of your query and influences:

The commands and operators used in the query.
The available evaluation metrics.
Explainable AI (XAI) options.

Kumo automatically determines the task type based on your Predictive Query (PQL).

Common Task Types

Task Type	Output	PQL Example
Regression	Continuous real number	`PREDICT customers.age FOR EACH customers.customer_id`
Binary Classification	True or False	`PREDICT fraud_reports.is_fraud FOR EACH transactions.id WHERE transactions.type = "bank transfer"`
Multiclass + Multilabel Classification	Class label	`PREDICT FIRST(purchases.type, 0, 7) FOR EACH users.user_id`
Link Prediction	List of items	`PREDICT LIST_DISTINCT(transactions.article_id, 0, 7) RANK TOP 10 FOR EACH customers.customer_id`

Examples

Regression

A regression task predicts a continuous value. For example, predicting the total amount of purchases per customer over the next 30 days:

PQL

PREDICT SUM(TRANSACTIONS.PRICE, 0, 30, days)
FOR EACH CUSTOMERS.CUSTOMER_ID

Kumo recognizes this as a regression task since it uses the SUM() operator without a boolean condition.

Binary Classification

A binary classification task predicts a true/false outcome. For example, predicting which customers will make no transactions in the next 30 days:

PQL

PREDICT COUNT(TRANSACTIONS.*, 0, 30, days) = 0
FOR EACH CUSTOMERS.CUSTOMER_ID

The = operator makes this a classification task.
Changing it to > would modify the positive label of the prediction.

For more Predictive Query examples across different task types, see the Predictive Query Examples.

Get Started

KumoRFM SDK

KumoRFM Fine-Tuning SDK

KumoRFM Fine-Tuning Platform

Common Task Types

Examples

Regression

Binary Classification

​Common Task Types

​Examples

​Regression

​Binary Classification

Common Task Types

Examples

Regression

Binary Classification