Question

Difference between classification and prediction in data mining in tabular form

Answer 1

There are two forms of data analysis that can be used for extracting models describing important classes or to predict future data trends. These two forms are as follows −

Classification

Prediction

Classification models predict categorical class labels; and prediction models predict continuous valued functions. For example, we can build a classification model to categorize bank loan applications as either safe or risky, or a prediction model to predict the expenditures in dollars of potential customers on computer equipment given their income and occupation.

What is classification?

Following are the examples of cases where the data analysis task is Classification −

A bank loan officer wants to analyze the data in order to know which customer (loan applicant) are risky or which are safe.

A marketing manager at a company needs to analyze a customer with a given profile, who will buy a new computer.

In both of the above examples, a model or classifier is constructed to predict the categorical labels. These labels are risky or safe for loan application data and yes or no for marketing data.

What is prediction?

Following are the examples of cases where the data analysis task is Prediction −

Suppose the marketing manager needs to predict how much a given customer will spend during a sale at his company. In this example we are bothered to predict a numeric value. Therefore the data analysis task is an example of numeric prediction. In this case, a model or a predictor will be constructed that predicts a continuous-valued-function or ordered value.

Note − Regression analysis is a statistical methodology that is most often used for numeric prediction

Answer 2

Classification vs. Prediction

Classification:

1. Determines the class of an element in datasheet.
2. Data here is grouped in categories.
3. Concerned about the class label.
4. Identifies the class label and using that class label classification model is created.

Prediction:

1. Determines missing or unknown element in a datasheet.
2. Classification model is built to predict the outcome.
3. Does not depend on class label.
4. Predictions are made using both regression ans classification models.