What is Feature?Feature kya hai?

🧸 Think of it likeAise samjho

Like the clues a property dealer uses to guess a flat's price: size, floor, area and distance from the station.Jaise property dealer flat ki keemat andaaza lagaane ke liye clues use karta hai: size, floor, area aur station se doori.

📘 ExplainedVistaar se

Features are the columns a model learns from; the label is the answer it predicts. Good features carry real signal and are available at prediction time. Raw data usually needs to be turned into features: ratios, counts over time windows, encoded categories.Features woh columns hain jinse model seekhta hai; label woh jawaab hai jo woh predict karta hai. Acche features mein asli signal hota hai aur prediction ke time available hote hain. Raw data ko aksar features mein badalna padta hai: ratios, time windows mein ginti, encoded categories.

💡 Real exampleAsli example

For house prices: area, bedrooms, distance to metro station.Ghar ki keemat ke liye: area, bedrooms, metro station se doori.

📖 Learn it step by stepStep by step seekho

• How machines learn: features, labels and trainingMachines kaise seekhti hain: features, labels aur training
• Feature engineering: turning raw data into useful inputsFeature engineering: raw data ko kaam ke inputs mein badalna

🔗 Related termsJude hue shabd

• Feature engineeringTurning raw data into useful model inputs, often using domain knowledge.Raw data ko model ke kaam ke inputs mein badalna, aksar domain knowledge se.
• LabelThe correct answer for an example, which a supervised model learns to predict.Example ka sahi jawaab, jise supervised model predict karna seekhta hai.
• Data leakageWhen information that won't exist at prediction time sneaks into training, making test scores falsely high.Jab prediction ke time na hone wali information training mein ghus jaati hai, aur test scores jhooth mein ooche aate hain.