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Machine Learning: Feature Selection and Dimensionality Reduction

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Machine Learning: Feature Selection and Dimensionality Reduction

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Questions and Answers

What is the primary goal of feature selection in predictive modeling?

To visualize high-dimensional data

To identify the most relevant features to predict a target variable (correct)

To increase the accuracy of the model

To reduce the number of features in the dataset

What is the purpose of ranking features based on their chi-squared scores in the filter method?

To eliminate the least contributing features

To select the top 10 features with the highest scores (correct)

To visualize the feature importance

To identify the most correlated features

What is the benefit of dimensionality reduction in terms of model performance?

It reduces the accuracy of the model

It has no impact on model performance

It increases the risk of overfitting

It mitigates the risk of overfitting (correct)

What is the main advantage of using recursive feature elimination (RFE) in the wrapper method?

It eliminates the least contributing features iteratively Signup and view all the answers

What is a benefit of dimensionality reduction in terms of data analysis?

It reduces the processing time for high-dimensional data Signup and view all the answers

What is a key concern in ensuring individuals' rights in data mining?

Clarifying ownership and control of data Signup and view all the answers

What is a major challenge in anonymizing data?

Balancing anonymization with the risk of re-identification Signup and view all the answers

Which of the following is a crucial aspect of transparency in data mining?

Holding entities accountable for outcomes Signup and view all the answers

What is a primary concern in ensuring fairness in data mining?

Addressing bias in data Signup and view all the answers

What is the main goal of regulatory compliance in data mining?

Adhering to relevant laws and regulations Signup and view all the answers