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Machine-learning Questions Set 7:

Quiz Mode

What is the name of the algorithm used to build decision trees?

Gradient descent

ID3

Naive Bayes

K-means

Solution:

Which of the following is NOT a key assumption of linear regression?

Homoscedasticity

Linearity

Normality

Heteroscedasticity

Solution:

Which of the following is NOT a key assumption of linear regression?

Homoscedasticity

Linearity

Normality

Heteroscedasticity

Solution:

Which of the following methods can be used to handle missing data in linear regression?

Imputation

Deletion

Both a and b

Neither a nor b

Solution:

Which of the following is a popular algorithm for anomaly detection in unsupervised learning?

Apriori

Gradient descent

DBSCAN

Isolation Forest

Solution:

Which of the following is an example of a decision tree-based algorithm that can handle both categorical and numerical data?

C4.5

CART

ID3

Naive Bayes

Solution:

In multiple linear regression, the VIF (variance inflation factor) is used to detect which of the following?

Multicollinearity

Heteroscedasticity

Non-normality

Outliers

Solution:

What is the purpose of pruning a decision tree?

To add more branches to the tree

To remove unnecessary branches from the tree

To change the structure of the tree

To add more data to the tree

Solution:

What is the purpose of the kernel trick in support vector machines?

To increase the number of features in the data

To decrease the number of features in the data

To transform the data into a higher-dimensional space

To transform the data into a lower-dimensional space

Solution:

The R-squared value of a linear regression model represents:

The percentage of the variance in the predictor variable(s) explained by the response variable

The degree of correlation between the predictor variable(s) and the response variable

The accuracy of the predictions made by the model

The percentage of the variance in the response variable explained by the predictor variable(s)

Machine-learning Questions Set 7:

What is the name of the algorithm used to build decision trees?

Solution:

Which of the following is NOT a key assumption of linear regression?

Solution:

Which of the following is NOT a key assumption of linear regression?

Solution:

Which of the following methods can be used to handle missing data in linear regression?

Solution:

Which of the following is a popular algorithm for anomaly detection in unsupervised learning?

Solution:

Which of the following is an example of a decision tree-based algorithm that can handle both categorical and numerical data?

Solution:

In multiple linear regression, the VIF (variance inflation factor) is used to detect which of the following?

Solution:

What is the purpose of pruning a decision tree?

Solution:

What is the purpose of the kernel trick in support vector machines?

Solution:

The R-squared value of a linear regression model represents:

Solution:

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