In a statistical sense with knowing pdf of features the best classifier is the Bayesian classifier. methods like linear, quadratic, svm, neural networks, fuzzy, knn and so on. with huge training samples. Maximal margin classifiers like SVM have a bounded generalization error.
How do you choose the best classifier?
Here are some important considerations while choosing an algorithm.
- Size of the training data. It is usually recommended to gather a good amount of data to get reliable predictions. ...
- Accuracy and/or Interpretability of the output. ...
- Speed or Training time. ...
- Linearity. ...
- Number of features.
Which is the best classifier algorithm?
Top 5 Classification Algorithms in Machine Learning
- Logistic Regression.
- Naive Bayes.
- K-Nearest Neighbors.
- Decision Tree.
- Support Vector Machines.
