What is Gradient boosting?Gradient boosting kya hai?

🧸 Think of it likeAise samjho

Like a student who, after each mock test, studies only the questions they got wrong. Many small rounds add up to a strong result.Jaise student har mock test ke baad sirf galat sawaalon ko padhta hai. Kai chhote rounds milkar strong result dete hain.

📘 ExplainedVistaar se

Gradient boosting is usually the strongest choice for tabular business data: fraud, churn, credit risk, pricing. Key settings are the number of trees, depth and learning rate; use early stopping on validation data. Libraries: XGBoost, LightGBM, CatBoost.Tabular business data ke liye gradient boosting aksar sabse mazboot choice hai: fraud, churn, credit risk, pricing. Zaroori settings: trees ki ginti, depth aur learning rate; validation data pe early stopping lagao. Libraries: XGBoost, LightGBM, CatBoost.

💡 Real exampleAsli example

An XGBoost model on 40 features raising fraud recall from 0.62 to 0.81.40 features pe XGBoost model se fraud recall 0.62 se 0.81.

📖 Learn it step by stepStep by step seekho

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

🔗 Related termsJude hue shabd

• Decision treeA model that predicts by asking a series of yes or no questions about the input.Model jo input ke baare mein haan ya nahi sawaalon ki ek series poochh kar predict karta hai.
• 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.
• Early stoppingStopping training when the validation score stops improving, to avoid overfitting.Validation score sudharna band ho to training rok dena, overfitting se bachne ke liye.