Anomaly

As explained in The Art of AI Product Development

An outlier is a data point whose behavior or value is anomalous relative to the dominant patterns in a dataset.

An anomaly is a sudden, unexpected deviation from typical behavior. In time-series data, it may appear as an extreme peak or trough; a short-lived spike may prove to be an outlier rather than a real trend. section 4.3.2 section 4.3.1

Unusual activity on an e-commerce site

A user who clicks endlessly without buying does not fit the discovered customer clusters. Investigating the behavior revealed a bot scraping the site, prompting the team to alert security. An anomaly is a signal to investigate, not an explanation by itself. section 4.1.6

Figure 4.6 Anomalies can show up as extreme peaks or troughs in the data.

Extreme peaks and troughs can make anomalies visible in a time series. section 4.3.2

How The Art of AI Product Development covers it

How deep it goes

Defines anomalies as unexpected departures and illustrates peaks, troughs, and unmatched users without detailing detection algorithms.

Examples

Uses unusual clicking by a new user, a bot outside customer clusters, and a brief traffic spike as examples.

What you can do after

Diagnose unusual activity by investigating deviations, as with a user whose repeated clicks revealed a site-scraping bot.

How it connects

Connects anomalies to time-series analysis, clustering, and outlier filtering.

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Related concepts

• out-of-distributionincludes · Out-of-distribution describes data or inputs whose generating distribution differs materially from the distribution represented in a model’s training data.
• local outlierincludes · A local outlier is a data item that differs from other items in its nearby or comparable cluster while belonging to a common overall type.
• winsorizationaddressed by · Winsorization is a data transformation that replaces extreme observations beyond selected thresholds with less-extreme boundary values rather than removing them.
• interquartile rangeuses · The interquartile range is the difference between the third and first quartiles of a distribution, measuring the spread of its middle half.
• box-and-whisker plotused by · A box-and-whisker plot is a statistical graphic that summarizes a numerical distribution using quartiles, a median, and whiskers or markers indicating spread and potential outliers.
• contextual anomalyincludes · A contextual anomaly is an observation that is anomalous relative to its surrounding temporal, situational, or other contextual conditions.

This explainer was generated by Manning's knowledge graph from the text of The Art of AI Product Development. The section links point to the parts of the book it draws on.