AI dictionary · Machine learning
What is F1 score?F1 score kya hai?
F1 score: One number that balances precision and recall.Ek number jo precision aur recall ko balance karta hai.
🧸 Think of it likeAise samjho
Like judging a fisherman on two things at once: how many of the fish in the lake he caught, and how much of his catch was actually fish and not old shoes.Machhuaare ko do cheezon pe ek saath parakhna: jheel ki kitni machhliyaan pakdi, aur jo pakda usmein kitna sach mein machhli tha, purane joote nahi.
📘 ExplainedVistaar se
F1 is the harmonic mean of precision and recall, so it's high only when both are reasonably high. It's handy for comparing models on imbalanced data, but in real decisions you usually pick a threshold based on which mistake costs more, rather than maximising F1 blindly.F1 precision aur recall ka harmonic mean hai, isliye yeh tabhi ooncha hota hai jab dono theek theek oonche hon. Imbalanced data pe models compare karne mein kaam ka hai, par asli faislon mein aksar threshold is hisaab se chunte ho ki kaunsi galti mehngi hai, F1 ko aankh band karke badhaane ke bajaye.
💡 Real exampleAsli example
Precision 0.8 and recall 0.6 give F1 of about 0.69.Precision 0.8 aur recall 0.6 se F1 lagbhag 0.69.
📖 Learn it step by stepStep by step seekho
🔗 Related termsJude hue shabd
Questions people ask
What is F1 score?
One number that balances precision and recall. F1 is the harmonic mean of precision and recall, so it's high only when both are reasonably high. It's handy for comparing models on imbalanced data, but in real decisions you usually pick a threshold based on which mistake costs more, rather than maximising F1 blindly.
How can I understand F1 score in simple words?
Like judging a fisherman on two things at once: how many of the fish in the lake he caught, and how much of his catch was actually fish and not old shoes.
What is an example of F1 score?
Precision 0.8 and recall 0.6 give F1 of about 0.69.
F1 score ka matlab kya hai?
Ek number jo precision aur recall ko balance karta hai. Machhuaare ko do cheezon pe ek saath parakhna: jheel ki kitni machhliyaan pakdi, aur jo pakda usmein kitna sach mein machhli tha, purane joote nahi.
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