How deeply does Machine Learning System Design cover diversity?

Defines a category-count baseline, but defers a fuller definition and alternative approaches to UX research.

Diversity

As explained in Machine Learning System Design

A measure of how varied the items or categories represented in a set of results are.

A search engine can optimize clicks and purchases yet still show repetitive results. Diversity measures how many different image categories appear on the results page. section 5.3.2

Use diversity as a practical baseline when evaluating search results:

Count the different image categories represented on the SERP. section 5.3.2
Measure it offline without additional data or recurring collection costs. section 5.3.2
Treat the category count as a starting point rather than a complete definition; validate richer notions of variety with UX stakeholders. section 5.3.2

Stock-image search

A PhotoStock results page containing images from eight distinct categories receives a diversity score of eight under the baseline metric, regardless of clicks or purchases. section 5.3.2

How Machine Learning System Design covers it

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Also explained in

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Ensemble Methods for Machine LearningEnsemble diversity is the degree to which the component models in an ensemble make different predictions or capture different aspects of the data.
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Interview SpeakDiversity is the presence and recognition of differences among people, including differences in identity, abilities, personality, communication, and social background.
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Think Like a Software Engineering ManagerDiversity is the presence of varied identities, backgrounds, experiences, or perspectives within a group.
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Grokking AI Algorithms, Second EditionGenetic diversity is the variation in genetic makeup among individuals in a population.
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Deep Learning with Python, Third EditionIn ensemble learning, the degree to which models make different errors or rely on different evidence.
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Deep Learning with R, Third EditionDiversity is the degree to which models in an ensemble make different errors or rely on different aspects of the data.

Compare how 7 books explain diversity →

Related concepts

ensembleused by · An ensemble is a technique that combines or considers outputs from multiple models or component methods collectively to produce or assess a joint result.
precisioncontrasts with · Precision is the proportion of items identified as positive, selected, or retrieved that satisfy the relevant correctness or relevance criterion.
thresholdconfigured by · A threshold is a boundary value against which a quantity is compared to determine whether a condition is met or an action or decision is triggered.
diversity, equity, and inclusionpart of · Diversity, equity, and inclusion is an organizational principle and practice promoting representation, fairness, participation, and belonging for people with different identities and backgrounds.

This explainer was generated by Manning's knowledge graph from the text of Machine Learning System Design. The section links point to the parts of the book it draws on.