What Machine Learning problems does the Engine tackle?

This article briefly describes the types of Machine Learning problems that the AI & Analytics Engine can tackle.

The AI & Analytics Engine currently supports three types of Machine Learning problems, namely classification, regression, and clustering.

Classification (supervised learning)

Given an observation, predict which category it belongs to, from a set of categories.

Examples:

  • Binary classification -- Is an email spam or not (yes/no)?

  • Multi-class classification -- Which genre does a movie belong to (action, comedy, drama, fantasy, romance, etc.)

Regression (supervised learning)

Given an observation, predict a numeric outcome such as house price and taxi trip duration.

Tip: Still curious? For a detailed comparison between classification and regression, see this article.

Clustering (unsupervised learning)

Partition data in the way that similar entities are grouped into the same cluster.

Examples:

  • Segment customers into groups of similar characteristics to target

  • Group items in a search engine and show similar results for a query

Tip: You can find some typical methods and applications of clustering in this article.