A Data Scientist Is Building a Model to Predict Customer

question 142

Multiple Choice

A Data Scientist is building a model to predict customer churn using a dataset of 100 continuous numerical features. The Marketing team has not provided any insight about which features are relevant for churn prediction. The Marketing team wants to interpret the model and see the direct impact of relevant features on the model outcome. While training a logistic regression model, the Data Scientist observes that there is a wide gap between the training and validation set accuracy. Which methods can the Data Scientist use to improve the model performance and satisfy the Marketing team's needs? (Choose two.)

• A) Add L1 regularization to the classifier
• B) Add features to the dataset
• C) Perform recursive feature elimination
• D) Perform t-distributed stochastic neighbor embedding (t-SNE)
• E) Perform linear discriminant analysis

Explain the role of experience in concept formation.

Understand the significance of lexicon in language.

Recognize the role of cognitive biases and mental sets in problem-solving.

Comprehend the relationship between genetics, environment, and intelligence.

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Definitions:

Chocolate Manufacturer

A company or business involved in the process of making chocolate from raw cocoa beans, including roasting, grinding, and refining.

Low Cost

Offering or producing goods or services at a minimal expense, often used as a competitive strategy.

Labor

The collective term for workers or the workforce, especially considered as an economic group contributing to the production process.

Foreign Countries

Nations or sovereign states other than one's own, especially when considered in terms of international relationships or business.