I’m presenting here a summary I’ve written of the key concepts, illustrations, otpimisaton program and limitations for the most common types of algorithms. Don’t hesitate to drop a comment !
We’ll cover :
- Bayes classifier
- Linear Discriminant Analysis (LDA)
- Quadratic Discriminant Analysis (QDA)
- Naive Bayes Classifier
- Perceptron
- Logistic Regression
- K-Nearest Neighbors (KNN)
- Local Averaging
- Decision Tree
- Support Vector Machine (SVM)
- Bagging
- Random Forest
- Extra Trees
- Boosting
- Gradient Boosting
- Depth Based Models
- Depth KNN
Click on the image below to load the PDF summary :
