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Odds

Odds are the ratio of the probability of an event occurring to the probability of its complement.

How 3 Manning books explain it

Grokking Machine Learning

Odds are the ratio of the probability of an event occurring to the probability of it not occurring.

How it is used
Uses odds to introduce log-odds scores for weak learners in AdaBoost.
How deep it goes
Defines odds with a formula, gives two probability examples, and notes their range before moving to log-odds.
Examples
Illustrates odds with rolling a 1 on a die and a horse winning three of four races.
What you can do after
Evaluate an event’s odds from its probability and distinguish odds from probability.

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Statistics Every Programmer Needs

Odds express the ratio of the probability of an event to the probability of its complement.

How it is used
Expresses event likelihood as successes relative to failures when presenting or solving probability problems.
How deep it goes
Defines odds, supplies equivalent formulas, converts between odds and probability, and applies the distinction to dice and cards.
Examples
Uses coin flips, face cards, single-die outcomes, and two-dice events involving specified results and sums.
What you can do after
Apply probability formulas to convert between event probability and odds and solve elementary dice and card calculations.

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Ensemble Methods for Machine Learning

Odds are the ratio of the probability of an event to the probability of its complement.

How it is used
Uses odds to interpret binary-classification predictions and logistic-regression feature effects.
How deep it goes
Develops the probability ratio, log-odds, sigmoid link, and coefficient multipliers, without formal derivations.
Examples
Uses betting odds, diabetes diagnosis, and breast-cancer diagnosis to explain odds and feature-weight effects.
What you can do after
Evaluate/understand logistic-regression coefficients by converting changes in log-odds into odds multipliers.

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Related concepts

These guides are generated from the text of Manning books by Manning's knowledge graph and link to the sections they draw on. The full books are available on liveBook and at manning.com.