Intro to types of classification algorithms in Machine Learning

Types of classification algorithms in Machine Learning

In machine learning and statistics, classification is a supervised learning approach in which the computer program learns from the input data and then uses this learning to classify new observations. This data set may simply be bi-class (like identifying whether the person is male or female or that the mail is spam or non-spam) or it may be multi-class. Some practical examples of classification problems are: speech recognition, handwriting recognition, bio metric identification, document classification etc.

Here we have few types of classification algorithms in machine learning:

1. Linear Classifiers: Logistic Regression, Naive Bayes Classifier
2. Nearest Neighbor
3. Support Vector Machines
4. Decision Trees
5. Boosted Trees
6. Random Forest
7. Neural Networks

Naive Bayes Classifier (Generative Learning Model) :

It is a classification technique based on Bayes’ Theorem with the assumption of independence among predictors. In other words , a Naive Bayes classifiers assume that the presence of a particular feature in a class is unrelated to the presence of any other feature or that all of these…