What is the number of main Domains in Data Science?

a$.$

$7$

b$.$

$2$

c$.$

$3$

d$.$

$4$

Question $2$

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What is the use of Feature Selections Methods?

a$.$

All Combination of Features

b$.$

Smallest set of Features

c$.$

Largest Set of Features

d$.$

Mean Set of Features

Question $3$

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Feature Transformation is also known as $\_\_\_\_\_\_\_\_\_\_\_$

a$.$

Math Engineering

b$.$

Feature Engineering

c$.$

Filtering

d$.$

Regression Engineering

Question $4$

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Which one is incorrect for Wrapper Method?

a$.$

Forward Selection

b$.$

Elastic Net

c$.$

Backward Elimination

d$.$

Step$-$wise Selection

Question $5$

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Which is not a Feature Selection Technique?

a$.$

Wrapper Method

b$.$

Filter Method

c$.$

Selection Method

d$.$

Embedded Method

Question $6$

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Which one is not a Feature Selection Technique?

a$.$

ECA

b$.$

PCA

c$.$

ICA

d$.$

LDA

Question $7$

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Which one is not a type of Filter Method?

a$.$

LASSO

b$.$

Correlation

c$.$

ANOVA

d$.$

Square Test

Question $8$

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What type of algorithm is Random Forest?

a$.$

Boosting

b$.$

Lacking

c$.$

Bagging

d$.$

Backing

Question $9$

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The Decision Tree represents a $\_\_\_\_\_\_\_\_\_\_-$like structure.

a$.$

Flower

b$.$

Leaves

c$.$

Tree

d$.$

Plant

Question $10$

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What is the use of the Random Forest Algorithm?

a$.$

solve problems

b$.$

handle Classification & Regression Problems

c$.$

handle Classification Problems

d$.$

handle Regression Problems

Question $11$

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Which one is another name for Bagging?

a$.$

Entropy

b$.$

Information Gain

c$.$

Bootstrap

d$.$

Bootstrap, Aggregation

Question $12$

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Which one is not a type of Ensemble?

a$.$

Graph Canonical Ensemble

b$.$

Micro$-$canonical Ensemble

c$.$

Canonical Ensemble

d$.$

Grand Canonical Ensemble

Question $13$

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$\_\_\_\_\_\_\_\_\_\_\_\_$ is a measure of the linear relationship between $2$ or more variables.

a$.$

Decision Tree

b$.$

Correlation

c$.$

Map

d$.$

Information Gain

Question $14$

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$\_\_\_\_\_\_\_\_\_\_\_\_$ works are exactly opposite to the Forward Feature Selection method. It starts with all the features available and builds a model.

a$.$

Backward Feature Elimination

b$.$

Feature Selection

c$.$

Forward Selection

d$.$

Best Fit

Question $15$

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Which one is the correct sequence to apply Regression Analysis?

a$.$

Analysis, Specification, Collection, Estimation, Assessment

b$.$

Analysis, Assessment, Specification, Collection, Estimation

c$.$

Specification, Analysis, Collection, Estimation, Assessment

d$.$

Specification, Collection, Estimation, Analysis, Assessment

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Which statement is true for Wrapper methods?

a$.$

Never Use

b$.$

useful mainly when the machine is black box

c$.$

Always prone to overfitting

d$.$

Use whenever possible as computationally efficient

Question $17$

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Which one is incorrect to remove Overfitting?

a$.$

Regularisation

b$.$

Cross$-$validation

c$.$

Embedding

d$.$

Ensembling