Question

Explain the following models and why they are used for data analysis

- regression model

- classification model

- decision tree model

Answer 1

1. Regression model: This model is useful for prediction and forecasting and can be used to infer the causal relationship between dependent and independent variables.

Example: Do education and IQ affect earnings? Here earning is the dependent variable and IQ and education are the independent variables.

2. Classification model: This model is useful to identify to which a set of categories, a new observation belongs, i.e. mainly used for discrete output variables where the regression mainly used for continuous variables.

Example: Spam detection in emails.

3. Decision tree model: This model is a predictive modeling approach, mainly used for datamining and machine learning. Tree models are used when the target variable can take discrete set of values: classification tress and also continuous set of values: regression tress.

Example: Customer satisfaction.