IAI Actuarial Core Principles · Risk Modelling and Survival Analysis · Elementary principles of machine learning

A health insurer in Pune has records of 50,000 past policyholders, each with age, BMI, smoking status and a recorded label showing whether a hospitalisation claim above ₹2 lakh occurred in the year. It wants a model to predict this label for new applicants. Which type of machine learning does this describe?

This is supervised learning. The insurer has labelled historical data, with a known claim outcome for each policyholder, and wants to predict that outcome for new applicants. Using inputs to predict a known target is the defining feature of supervised learning, and here it is a classification problem.

ASupervised learningCorrect
BUnsupervised learning
CReinforcement learning
DDimension reduction using principal components
Cluster analysis

Explanation

The data include a known target label (claim above ₹2 lakh or not) for each past case, and the goal is to predict that label for new cases. Learning from labelled examples is supervised learning, here a classification task. Unsupervised methods like clustering or PCA do not use a response label.

Did you get it right without looking?

One question tells you little. A timed set on Elementary principles of machine learning shows your real accuracy, how long you take and where you lose marks.

Practise Elementary principles of machine learning Free diagnostic mock

More Elementary principles of machine learning questions