AI dictionary · Machine learning
What is AUC?AUC kya hai?
Also called: Area under the curve
AUC: A single number summarising how well a model separates positives from negatives across all thresholds.Ek number jo batata hai model saare thresholds pe positives ko negatives se kitna acche se alag karta hai.
🧸 Think of it likeAise samjho
Like checking how well a guard can tell thieves from shoppers: pick one thief and one shopper at random, and AUC is how often the guard rates the thief as more suspicious.Jaise check karna ki guard chor aur customer mein kitna farak kar paata hai: ek chor aur ek customer random chuno, AUC batata hai ki kitni baar guard chor ko zyada shaky maanta hai.
📘 ExplainedVistaar se
ROC AUC is the chance that the model scores a random positive higher than a random negative: 0.5 is guessing, 1.0 is perfect. PR AUC summarises precision and recall together and is more informative when positives are rare, like fraud. AUC doesn't pick a threshold for you; you still choose one for the business trade off.ROC AUC woh chance hai ki model ek random positive ko random negative se zyaada score de: 0.5 matlab andaaza, 1.0 matlab perfect. PR AUC precision aur recall ko saath mein summarise karta hai aur tab zyaada kaam ka hai jab positives rare hon, jaise fraud. AUC aapke liye threshold nahi chunta; business trade off ke liye threshold aapko khud chunna hai.
💡 Real exampleAsli example
A fraud model with ROC AUC 0.92 ranks fraud above normal payments 92% of the time.ROC AUC 0.92 wala fraud model 92% baar fraud ko normal payments se upar rank karta hai.
📖 Learn it step by stepStep by step seekho
🔗 Related termsJude hue shabd
Questions people ask
What is AUC?
A single number summarising how well a model separates positives from negatives across all thresholds. ROC AUC is the chance that the model scores a random positive higher than a random negative: 0.5 is guessing, 1.0 is perfect. PR AUC summarises precision and recall together and is more informative when positives are rare, like fraud. AUC doesn't pick a threshold for you; you still choose one for the business trade off.
How can I understand AUC in simple words?
Like checking how well a guard can tell thieves from shoppers: pick one thief and one shopper at random, and AUC is how often the guard rates the thief as more suspicious.
What is an example of AUC?
A fraud model with ROC AUC 0.92 ranks fraud above normal payments 92% of the time.
AUC ka matlab kya hai?
Ek number jo batata hai model saare thresholds pe positives ko negatives se kitna acche se alag karta hai. Jaise check karna ki guard chor aur customer mein kitna farak kar paata hai: ek chor aur ek customer random chuno, AUC batata hai ki kitni baar guard chor ko zyada shaky maanta hai.
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