SVD stands for $\_\_\_\_\_\_\_\_\_\_$

a$.$

Simple Vault Reality

b$.$

Simple Value Reduction

c$.$

Singular Value Reduction

d$.$

Singular Value Reality

Question $2$

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Predictive Modeling is a $\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_$ Technique.

a$.$

Static

b$.$

Straight

c$.$

Statistical

d$.$

Dimensional

Question $3$

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Define any Character, Number, or Quantity that can be counted.

a$.$

Vary

b$.$

Object

c$.$

Variable

d$.$

Thing

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Select the number of Levels in the Predictive Model.

a$.$

$4$

b$.$

$7$

c$.$

$5$

d$.$

$3$

Question $5$

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Which Algorithm provides a linear relationship between an independent variable and a dependent variable?

a$.$

Decision Tree

b$.$

SVD

c$.$

Linear Regression

d$.$

PCA

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PCA stands for $\_\_\_\_\_\_\_\_\_\_\_$

a$.$

Principal Company Analysis

b$.$

Principal Component Analysis

c$.$

Prime Company Analysis

d$.$

Prime Component Analysis

Question $7$

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Singular Value Decomposition of a matrix is a factorization of a matrix into $\_\_\_\_\_\_\_\_\_$matrices.

a$.$

Two

b$.$

Five

c$.$

Three

d$.$

Four

Question $8$

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Dimensionality Reduction is the transformation of Data from $\_\_\_\_\_\_\_\_$ to $\_\_\_\_\_\_\_\_\_$ dimension.

a$.$

Low, High

b$.$

Low, Medium

c$.$

Medium, Low

d$.$

High, Low

Question $9$

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A Hierarchical Data Structure defined as a collection of Nodes is called $\_\_\_$

a$.$

Chart

b$.$

Map

c$.$

Graph

d$.$

Tree

Question $10$

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What is the full form of LASSO?

a$.$

Less Absolute Shrinkage & Select Operator

b$.$

Least Absolute Shrinkage & Selection Operator

c$.$

Least About Simple & Selection Operator

d$.$

Left Absolute Simple Selection Operator

Question $11$

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Dimensionality reduction removes $\_\_\_\_\_\_\_\_$ in the data.

a$.$

values

b$.$

Noise

c$.$

images

d$.$

repetition

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A $\_\_\_\_\_\_$ number of dimensions in data means $\_\_\_\_$ training time and $\_\_\_\_\_$ computational and $\_\_\_\_\_$ the overall performance of algorithms.

a$.$

less, lower, less, increase

b$.$

less, less, lower, increase

c$.$

lower, less, less, increase

d$.$

lower, increase, less, less

Question $13$

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$\_\_\_\_\_\_\_\_$ is performed during pre$-$processing stage before building a model to improve the performance.

a$.$

Stemming

b$.$

Elimination

c$.$

Modeling

d$.$

Dimensionality Reduction

Question $14$

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Name the Analysis that works on the condition that while the data in a higher dimensional space is mapped to data in a lower dimension space, the variance of the data in the lower dimensional space should be maximum.

a$.$

LASSO

b$.$

SVD

c$.$

PCA

d$.$

PCN

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Which one is a physical quantity that is completely described by its magnitude?

a$.$

Scalar

b$.$

Force

c$.$

Velocity

d$.$

Variable

Question $16$

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Which is the correct sequence of steps for the PCA Algorithm?

a$.$

Collection, Calculate, Sort, Structure, Covariance, Standardize, Eigen Vectors & Values Sort, Calculate

b$.$

Collection, Calculate, Sort, Structure, Standardize, Covariance, Eigen Vectors & Values Sort, Calculate

c$.$

Collection, Structure, Standardize, Covariance, Eigen Vectors & Values, Sort, Calculate

d$.$

Collection, Sort, Calculate, Structure, Standardize, Covariance, Eigen Vectors & Values Sort, Calculate

Question $17$

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Which syntax is correct to check the correlation between various Components by using a heatmap?

a$.$

sns$.$heatmapp$($data$\_$pca.corre$())$

b$.$

sns$.$heatmap$($data$\_$pca.corr$())$

c$.$

sns$.$heatmap$($data$\_$pca.corre$())$

d$.$

sns$.$heatmap$($data$\_$pca.correl$())$