What is Decision tree?Decision tree kya hai?

🧸 Think of it likeAise samjho

Like the game '20 questions': each yes or no question narrows things down until you reach the answer.'20 questions' game jaisa: har haan ya na wala sawaal options kam karta hai jab tak jawaab na mil jaaye.

📘 ExplainedVistaar se

Each split picks the question that best separates the outcomes, like 'income above ₹50k?'. Trees are easy to explain but a single deep tree overfits. Random forests and gradient boosting combine many trees and are among the strongest models for tabular data.Har split woh sawaal chunta hai jo results ko sabse acche se alag kare, jaise 'income ₹50k se zyaada?'. Trees samjhaane mein aasaan hain par ek gehra tree overfit karta hai. Random forests aur gradient boosting kai trees jodte hain aur tabular data ke liye sabse mazboot models mein hain.

💡 Real exampleAsli example

Has the customer missed a payment? If yes, high risk; if no, check income next.Kya customer ne payment miss kiya? Haan to high risk; nahi to agla income check.

📖 Learn it step by stepStep by step seekho

• Decision trees, random forests and boostingDecision trees, random forests aur boosting

🔗 Related termsJude hue shabd

• Random forestMany decision trees trained on random samples whose votes are averaged.Random samples pe train hue kai decision trees jinke votes ka average liya jaata hai.
• Gradient boostingBuilding many small decision trees one after another, each fixing the previous ones' mistakes.Kai chhote decision trees ek ke baad ek banana, har ek pichhlon ki galtiyaan sudhaarta hai.