We all have used one of the following supervised learning algorithms for predictive analysis:

- Logistic Regression
- Ridge Regression
- LASSO Regression
- Linear Discriminant Analysis (LDA)
- K Nearest Neighbors (KNN)
- Naive Bayes (NB)
- Support Vector Machine (SVM)
- Decision Tree
- Random Forest (RF)
- Gradient Boosting

But have you thought of their pros or cons? Here I have listed few :

- 1. Logistic Regression
- 2. Ridge Regression
- 3. LASSO Regression
- 4. Linear Discriminant Analysis (LDA)
- 5. K Nearest Neighbors (KNN)
- 6. Naive Bayes (NB)
- 7. Support Vector Machine (SVM)
- 8. Decision Tre
- 9. Random Forest (RF)
- 10. Gradient Boosting

#classification #supervised-learning #regression #algorithms #machine-learning

1.60 GEEK