How deeply does Grokking AI Algorithms, Second Edition cover accuracy?

Defines overall correctness through a worked classification example, while noting other metrics reveal additional performance details.

Accuracy

As explained in Grokking AI Algorithms, Second Edition

An accuracy score is the proportion of evaluated predictions that match their correct outcomes.

Accuracy is the share of evaluated predictions that match the actual outcomes. For a classifier, it summarizes how often the model is correct overall. section 8.18

Measure it on examples the model has not seen during training: a score on training data can be misleading. Accuracy gives an overall view, so check other metrics when you need more detail about performance across classes. section 8.12 section 8.13 section 8.18

Diamond-cut predictions

In the ten-example test set, seven predicted cuts match the actual cuts, so the classifier is correct on seven of ten examples. section 8.18

Table 8.17 The diamond dataset for classification and predictions

	Carat	Price	Cut	Prediction
1	0.26	689	Okay	Okay	✓
2	0.41	880	Perfect	Perfect	✓
3	0.52	1,012	Perfect	Perfect	✓
4	0.76	907	Okay	Okay	✓
5	0.81	2,650	Okay	Okay	✓
6	0.90	2,634	Okay	Okay	✓
7	1.24	2,999	Perfect	Okay	✗
8	1.42	3,850	Perfect	Okay	✗
9	1.61	4,345	Perfect	Perfect	✓
10	1.78	3,100	Okay	Perfect	✗

Compare each predicted diamond cut with its actual cut to see which examples count as correct. section 8.18

How Grokking AI Algorithms, Second Edition covers it

Cover of Grokking AI Algorithms, Second Edition

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Related concepts

evaluatormeasured by · An evaluator is a model or component that assesses outputs against specified criteria and produces judgments, scores, comparisons, or feedback.
fidelitycontrasts with · Fidelity is the degree to which an output, model, or representation accurately reflects or is supported by its relevant source, target, evidence, or behavior.
language modelmeasures · A language model is a computational model that represents patterns in linguistic tokens to estimate sequence probabilities and predict or generate language from context.
classifiermeasures · A classifier is a predictive computational model that assigns inputs to one or more discrete classes or categories.
evaluation datasetmeasured by · An evaluation dataset is a collection of examples or test cases, often with expected or judged outcomes, designated to assess a model or system against defined criteria.
performancecontrasts with · Performance is the measurable effectiveness or operational behavior of a system under specified conditions, assessed through relevant qualities such as task results, speed, responsiveness, throughput, or resource use.

This explainer was generated by Manning's knowledge graph from the text of Grokking AI Algorithms, Second Edition. The section links point to the parts of the book it draws on.