Bernoulli trials are applicable to two-class classification (two outcomes).Group of answer choicesTrueFalse

Break Down the Problem

1. Understand Bernoulli Trials: Bernoulli trials refer to experiments or processes that can result in one of two outcomes, often called "success" and "failure."
2. Relate to Classification: Two-class classification involves categorizing data into one of two distinct classes or outcomes.

Relevant Concepts

1. Bernoulli Distribution: The outcomes of a Bernoulli trial are typically represented by a Bernoulli distribution, which has parameters indicating the probability of success $p$ (success) and the probability of failure $1-p$.

Analysis and Detail

1. Two-Class Classification: In the context of machine learning and statistics, two-class classification can be frame in terms of Bernoulli trials since each classification can be treated as a success (correct classification) or failure (incorrect classification).
2. Example in Classification: For instance, if you classify emails as "spam" or "not spam," each email can be considered a Bernoulli trial.

Verify and Summarize

1. Conclusion: Since Bernoulli trials specifically deal with two possible outcomes, they are indeed applicable to two-class classification problems.

Final Answer

True