DY0-001問題集、CompTIA実際の試験問題

質問 1

Which of the following is a key difference between KNN and k-means machine-learning techniques?

A. KNN operates exclusively on continuous data, while k-means can work with both continuous and categorical data.

B. KNN is used for classification, while k-means is used for clustering.

C. KNN is used for finding centroids, while k-means is used for finding nearest neighbors.

D. KNN performs better with longitudinal data sets, while k-means performs better with survey data sets.

正解: B

解説: (PassTest メンバーにのみ表示されます)

質問 2

Which of the following best describes the minimization of the residual term in a LASSO linear regression?

A. e

B. 0

C. |e|

D. e2

正解: D

解説: (PassTest メンバーにのみ表示されます)

質問 3

Which of the following modeling tools is appropriate for solving a scheduling problem?

A. Decision tree

B. One-armed bandit

C. Constrained optimization

D. Gradient descent

正解: C

解説: (PassTest メンバーにのみ表示されます)

質問 4

A data analyst wants to use compression on an analyzed data set and send it to a new destination for further processing. Which of the following issues will most likely occur?

A. Library dependency will be missing.

B. Server memory usage will be too high.

C. Server CPU usage will be too high.

D. Operating system support will be missing.

正解: C

解説: (PassTest メンバーにのみ表示されます)

質問 5

Which of the following best describes the minimization of the residual term in a ridge linear regression?

A. e

B. 0

C. |e|

D. e2

正解: D

解説: (PassTest メンバーにのみ表示されます)

質問 6

A data scientist receives an update on a business case about a machine that has thousands of error codes. The data scientist creates the following summary statistics profile while reviewing the logs for each machine:

Which of the following is the most likely concern with respect to data design for model ingestion?

A. Multivariate outliers

B. Insufficient features

C. Sparse matrix

D. Granularity misalignment

正解: C

解説: (PassTest メンバーにのみ表示されます)

質問 7

A statistician notices gaps in data associated with age-related illnesses and wants to further aggregate these observations. Which of the following is the best technique to achieve this goal?

A. Linearization

B. Label encoding

C. Binning

D. Imputing

正解: C

解説: (PassTest メンバーにのみ表示されます)

質問 8

A data scientist is building a proof of concept for a commercialized machine-learning model. Which of the following is the best starting point?

A. Model selection

B. Model performance evaluation

C. Hyperparameter tuning

D. Literature review

正解: D

解説: (PassTest メンバーにのみ表示されます)

質問 9

A data scientist is using the following confusion matrix to assess model performance:

The model is predicting whether a delivery truck will be able to make 200 scheduled delivery stops. Every time the model is correct, the company saves an hour in planning and scheduling of maintenance work. Every time the model is wrong, the company loses four hours of delivery time for the truck. Which of the following is the net model impact for the company?

A. 25 hours saved

B. 165 hours lost

C. 25 hours lost

D. 165 hours saved

正解: C

解説: (PassTest メンバーにのみ表示されます)

CompTIA DataAI Certification - DY0-001 模擬練習