Читать книгу Enterprise AI For Dummies - Zachary Jarvinen - Страница 40

Machine learning via unsupervised classification uses clustering and association algorithms to discover relationships in a heterogeneous dataset:

 Clustering algorithms identify commonalities in the data, such as textual content or data format, and extrapolate relationships to create natural groupings and detect anomalous elements, such as security threats or medical issues.

 Association algorithms reveal interesting relationships in the data to answer questions to address issues such as reducing customer churn or selecting related products for a promotion.

AI teams use unsupervised classification when attempting to answer these types of questions:

 Is there any evidence of fraud in these financial transactions?

 Are there any network performance symptoms that indicate a latent issue that would increase the risk of network failure?

 Are there any anomalies in customer activity that point to possible buying trends?