Page 254 - Touhpad Ai

AT A GLANCE

Data modelling is like making a plan or a blueprint for how data will be stored and used in a system.
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¥ Data models are created based on what a business or organisation needs.
¥ There are various types of data models – hierarchical, dimensional, relational and entity-relational.
¥ Data modelling helps different people—like developers, data experts, and business teams—see and understand
how data is connected in a database or data system.
Regression is a Supervised Machine Learning algorithm used to analyse the relationship among dependent
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variable (target) and independent variable (predictor). It predicts the output values based on input values.
Regression is basically used when the dependent variable is of a continuous data type. The independent
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variables, on the other hand, can be of any data type—continuous, nominal/categorical etc.
There are several types of regression analysis, random forest regression, support vector regression, decision
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tree regression, linear regression, polynomial regression, ridge regression, lasso regression and logistic
regression.

EXERCISE

Solved Questions
SECTION A (Objective Type Questions)
AI QUIZ
A. Tick (ü) the correct option.
1. In the linear regression equation y = mx+b, m represents .

a. Estimated or predicted response b. Independent variable
c. Estimated slope d. Estimated intercept

2. In the linear regression equation y = mx+b, b represents .
a. Slope of the line b. Independent variable
c. Dependent variable d. Y-intercept

3. Which of the following represents the difference between the observed and predicted values in regression?
a. m (slope) b. Residual error (e)

c. x-intercept d. y-intercept

4. A regression between house price (dependent variable in lakhs) and house size (independent variable in square
metres) for 40 houses resulted in the following equation:
y = 9.2 + 0.25x

If a house measures 80 square metres, what is the predicted price of the house?
a. `28.2 lakhs b. `27.2 lakhs
c. `30.0 lakhs d. `29.2 lakhs

252 Touchpad Artificial Intelligence - XI