Machine learning algorithms

Machine learning algorithms

Basically machine learning algorithms are divided into two categories

1) Supervised learning

2) Unsupervised learning

In supervised learning data is labelled through which algorithms can learn (train data) and then apply the learnings to new data. For eg. Suppose we have house price data of 1000 houses and basis on that we have to predict the price of other houses so in this case the price of houses is the labelled data which is called as dependent variable while all other variables such as area of house, no of rooms, carpet area, etc. are called as independent variables.

While in unsupervised learning we don't have labelled data and therefore we use algorithms to understand the pattern of data.

List of algorithms

Supervised learning

1) Linear regression

2) Logistic regression

3) Classification tree

4) Random forest

5) Support vector machine

6) Naive Bayes

7) KNN (K nearest neighbour)

8) Neural network

Unsupervised learning

1) K-means clustering

Aproiri algorithm

1) Market basket analysis