Difference between Classification, Clustering and Regression with examples and applications.


Difference between Classification, Clustering and Regression with examples and applications.


CLASSIFICATION
If the prediction value tends to be category like yes/no etc then it falls under classification type.

Examples
1.     Check if image belongs to class ‘face ‘ or ‘cat’
2.     Check if an animal is mammal or reptile
3.     Find classes like good harvest or bad harvest.
4.     Identify if a news is related to politics, sports etc.
5.     Identify if an image is a male/female/child face.
6.     Email is spam or not.
7.     Identify the patient is ill or not.
8.     Matching Aadhar card to a template.
9.     Checking to see if a currency inserted in an ATM is fake or real.

CLUSTERING
Grouping similar data to given number of clusters.

Examples
1.     Find all transactions which are fraudulent in nature.
2.     Given a news report, group similar news together.
3.     Movie recommendations.
4.     Product categorization.
5.     Grouping similar color pixels in an image.
REGRESSION
Regression is mostly used for predicting values.

1.     Find the number of kgs of rice produced given some climatic conditions and rain data.
2.     How tall is a man?
3.     How many customers has viewed daily experience?
4.     Given information about the bungalow, predict the price.
5.     Netflix – Given a user and movie, predict the rating of the movie.
6.     Predicting the number of likes on Facebook post given time, week and usual likes of the person.
7.     Predict stock market price.
8.     Predicting the price of a product based on the market conditions, economy and brand image.
To find classes or categories use classification
To group data, use clustering.
To find value, use regression

Usually classification and regression are considered as supervised learning.
Clustering and association are unsupervised learning.


Difference between Classification, Clustering and Regression with examples and applications.