Unsupervised Learning

Unsupervised learning is where you put data X and no corresponding output variable.The goal for unsupervised learning is to model the under lying structure or distribution in the data in order to learn more about the data, in simple words in unsupervised learning approach the data instances of a training data set do not have an expected output Associated to them instead of unsupervised learning algorithm detects pattern based on innate characteristics of the input data an example of machine learning tasks.Ask that applies unsupervised learning is clustering in this task similar data instance are grouped together in order to identify clusters of data.

ALGORITHM

1 K-MEAN ALGORITHM

 K-MEAN Algorithm hierarchical clustering now, suppose a friend invites you to his party and where you meet totally strangers.Now you will classify them using unsupervised learning as you don’t have any prior knowledge about them and classification can be done on basis of gender age group dressing education qualification or whatever way you might like now way why this learning is different from supervised learning since you didn’t use any past a prior knowledge about the people you kept on classify them on the go as they kept on coming you kept on classifying them.let’s suppose you have never seen a football match before and by chance you watch a video on internet.Now you can easily classify the player on the basis of different criterion,like players wearing same kind of kit are in one class player wearing different kinds of kit are different class.Unsupervised learning are also used in sectors as well like banking health care.So in banking sector it is used to segment customers by behavioral characteristic by surveying prospects and customers to develop multiple segment using clustering and health care sector.It is used categorize the MRI data by normal or abnormal.Ages it uses deep learning technique to a build a model that learn from different feature of images to recognize a different pattern.