# Predictive Model

## Model

• A simplified representation of reality created to serve a purpose.

• E.g., Map, Architectural blueprint, Engineering prototype Mathematical Model

• E.g., a formula: V=IR

## Prediction

• To estimate an unknown value (target variable)

## Predictive Model

• To setup a formula for estimating an unknown value (target variable) of interest

• Supervised Learning

• It is often built and tested using events from historical data.

• Usage Example

• Predictive models for spam filtering estimate whether a given piece of email is spam.
• Predictive Model Form
• Mathematical Form
• Logical statement such as a rule
• But often it is a hybrid of the two
• Predictive Model Type

• Classification models
• Class-probability estimation models
• Regression models
• Predictive Modeling
• To create a model which describes a relationship between a set of selected variables (attributes or features) and a target variable.
• It estimates the value of the target variable as a function of the selected variables [Source: Data Science for Business]

• Terminology
• Instance (or Example)
• a fact or a data point
• Feature Vector (or Row)
• Attributes
• An instance is described by a set of attributes (or fields, columns, variables, or features)
• Independent variables or predictors
• Target Variable
• Dependent variable

## Model Induction

• Induction
• A term from philosophy that refers to generalizing from specific cases to general rules (or laws, or truths).
• Model Induction
• The creation of models from data
• Most inductive procedures have variants that induce models both for classification and for regression.
• Training Data
• The input data for the induction algorithm, used for inducing the model
• They are also called labeled data
• Induction vs. Deduction
• Deduction starts with general rules and specific facts, and creates other specific facts from them.
• The use of our models can be considered a procedure of deduction.