Interview question: What are the various classification algorithms?

In an earlier post I covered the question, ‘What is machine learning’, and that blog post can be read here:- https://medium.com/@tracyrenee61/interview-question-what-is-machine-learning-d042efc7569e

Machine learning is composed of four types of learning techniques, being:-

1. Supervised learning (with labels)
2. Unsupervised learning (without labels)
3. Semi-supervised learning (partially labelled)
4. Reinforcement learning (learn by trial and error)

Supervised learning is a sub-type of machine learning where the datasets are labelled.

There are two types of supervised learning, being:-

1. Classifications (labels are discrete values)
2. Regressions (labels are continuous)

In this blog post I intend to discuss some of the various classification algorithms, which are:-

1. Linear algorithms
2. Decision trees
3. Support vector machine
4. Kernel estimator
5. Quadratic
6. Naive Bayes
7. Logistic regression
8. Perceptron