In DBSCAN, what is a 'core point'?

A point that is the center of the cluster

A point that has at least a minimum number of neighbors within a specified radius

A point that is on the boundary of a cluster

A point that is far from all other points

What is the purpose of cross-validation?

To reduce the number of hyperparameters

To select the best features for the model

To increase the size of the training dataset

To evaluate a model's generalization performance

A data science practitioner is training a regression model to predict house prices. They choose XGBoost regression. Which statement best describes how XGBoost builds the model?

It trains many independent trees on bootstrap samples and averages their predictions to reduce variance.

It fits a linear model to the features and then applies a non-linear transformation to the output to capture complex patterns.

It fits a single deep decision tree to the entire training set and averages the leaf predictions.

It trains an ensemble of trees sequentially, where each new tree corrects the residual errors of the previous ensemble using gradient descent on a loss function.

CertNexusCertified Data Science Practitioner (CDSP)

Domain 4Objective 2

Objective 4.2 Train Models CERTIFIED-DATA-SCIENCE-PRACTITIONER Practice Questions (Page 3)

Part of the 4.0 Building models domain, which accounts for 19-27% of the CERTIFIED-DATA-SCIENCE-PRACTITIONER exam.

43questions here

9free pages

18concepts

19-27%of the exam

Questions 11–15

11foundation · easy
In DBSCAN, what is a 'core point'?
Select an answer first
12foundation · easy
What is the purpose of cross-validation?
Select an answer first
13application · medium
A credit card company wants to build a model to predict whether a transaction is fraudulent (yes/no). The dataset is highly imbalanced, with very few fraudulent transactions. The team needs a model that can handle this imbalance and provide probability scores. Which model is most appropriate?
Select an answer first
14foundation · medium
A data science practitioner is training a regression model to predict house prices. They choose XGBoost regression. Which statement best describes how XGBoost builds the model?
Select an answer first
15application · medium
A biologist wants to understand the evolutionary relationships between different species based on genetic data. They need a visual representation of how species are grouped and nested. Which clustering approach is most appropriate?
Select an answer first

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Objective 4.2 Train Models CERTIFIED-DATA-SCIENCE-PRACTITIONER Practice Questions (Page 3)

Questions 11–15

In DBSCAN, what is a 'core point'?

What is the purpose of cross-validation?

A credit card company wants to build a model to predict whether a transaction is fraudulent (yes/no). The dataset is highly imbalanced, with very few fraudulent transactions. The team needs a model that can handle this imbalance and provide probability scores. Which model is most appropriate?

A data science practitioner is training a regression model to predict house prices. They choose XGBoost regression. Which statement best describes how XGBoost builds the model?

A biologist wants to understand the evolutionary relationships between different species based on genetic data. They need a visual representation of how species are grouped and nested. Which clustering approach is most appropriate?

Keep studying — 4.0 Building models