Difference between regression and classification model?

The difference between regression and classification models lies in the type of output they predict. Lang

Regression

• Goal: Predict a continuous numeric value

• Example Outputs: Price, temperature, age, salary

• Algorithms Used:

  • Linear Regression

  • Decision Tree Regression

  • Random Forest Regressor

  • XGBoost Regressor

Example Question:

What will be the house price given the size and location?

Classification

• Goal: Predict a category or class label

• Example Outputs: Yes/No, Spam/Not Spam, Disease/No Disease

• Algorithms Used:

  • Logistic Regression

  • Decision Trees

  • Random Forest Classifier

  • SVM

  • XGBoost Classifier

Example Question:

Will this email be classified as spam or not?

Summary Table

Feature	Regression	Classification
Output Type	Continuous value	Categorical label
Example Output	250.5, 75 kg, 98.7%	Yes/No, Red/Blue, Class A/B
Example Algorithm	Linear Regression, SVR	Logistic Regression, SVM