DY0-001 TEST VCE, DY0-001 EXAM QUIZ

DY0-001 Test Vce, DY0-001 Exam Quiz

DY0-001 Test Vce, DY0-001 Exam Quiz

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Tags: DY0-001 Test Vce, DY0-001 Exam Quiz, New DY0-001 Exam Pass4sure, New Exam DY0-001 Materials, Test DY0-001 Guide Online

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CompTIA DataX Certification Exam Sample Questions (Q77-Q82):

NEW QUESTION # 77
A team is building a spam detection system. The team wants a probability-based identification method without complex, in-depth training from the historical data set. Which of the following methods would best serve this purpose?

  • A. Logistic regression
  • B. Linear regression
  • C. Random forest
  • D. Naive Bayes

Answer: D

Explanation:
# Naive Bayes is a probabilistic classification algorithm based on Bayes' theorem. It is lightweight, fast, and effective for text-based classification problems like spam detection. It also performs well with small or simple training sets.
Why the other options are incorrect:
* A: Logistic regression is also probabilistic but requires more feature preprocessing.
* B: Random forest is accurate but computationally heavier.
* D: Linear regression is for continuous targets - not suitable for classification.
Official References:
* CompTIA DataX (DY0-001) Study Guide - Section 4.1:"Naive Bayes classifiers are ideal for spam detection and similar applications due to their efficiency and probabilistic nature."
* Text Classification Techniques, Chapter 4:"Naive Bayes requires minimal training and works well with high-dimensional, sparse data such as email content."


NEW QUESTION # 78
A data scientist wants to digitize historical hard copies of documents. Which of the following is the best method for this task?

  • A. Word2vec
  • B. Optical character recognition
  • C. Latent semantic analysis
  • D. Semantic segmentation

Answer: B

Explanation:
# Optical Character Recognition (OCR) is the process of converting scanned images or hard copy text into machine-encoded text. It is the standard technique for digitizing printed or handwritten content.
Why the other options are incorrect:
* A: Word2vec is for generating word embeddings from digital text.
* C: Latent Semantic Analysis analyzes semantic structure of existing digital documents.
* D: Semantic segmentation is used in image processing for pixel-wise classification - not text extraction.
Official References:
* CompTIA DataX (DY0-001) Official Study Guide - Section 6.3:"OCR converts scanned physical documents into text files that can be searched, analyzed, or stored digitally."
* Practical NLP Applications, Chapter 2:"OCR is a prerequisite for turning printed or written material into structured data suitable for text analytics."
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NEW QUESTION # 79
The most likely concern with a one-feature, machine-learning model is high error due to:

  • A. bias
  • B. dimensionality
  • C. variance
  • D. probability

Answer: A

Explanation:
# A one-feature model is likely to be overly simplistic and may not capture the true complexity of the target variable. This leads to underfitting, which is associated with high bias - the model consistently misses the mark regardless of the data.
Why the other options are incorrect:
* B: High dimensionality is not a concern in this case - the model has too few features.
* C: Variance refers to overfitting - more common in overly complex models.
* D: Probability is a modeling technique, not a source of error.
Official References:
* CompTIA DataX (DY0-001) Official Study Guide - Section 4.2:"Models with insufficient features tend to underfit and exhibit high bias due to their inability to represent complex relationships."
* Bias-Variance Tradeoff - Data Science Textbook:"A high-bias model makes strong assumptions and is typically too simple to capture the underlying patterns in data."


NEW QUESTION # 80
A data analyst wants to generate the most data using tables from a database. Which of the following is the best way to accomplish this objective?

  • A. RIGHT OUTER JOIN
  • B. INNER JOIN
  • C. LEFT OUTER JOIN
  • D. FULL OUTER JOIN

Answer: D

Explanation:
# FULL OUTER JOIN returns all rows from both tables, inserting NULLs where no match exists. This join includes the maximum possible number of records - all matches, plus all unmatched records from both sides.
Why the other options are incorrect:
* A: INNER JOIN returns only matching rows - less total data.
* B & C: LEFT/RIGHT JOIN include all rows from one table only.
Official References:
* CompTIA DataX (DY0-001) Study Guide - Section 5.2:"A FULL OUTER JOIN maximizes data volume by including all matched and unmatched records from both tables."
* SQL for Data Science, Chapter 4:"Use FULL OUTER JOIN when the goal is to preserve every record from both datasets regardless of match."
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NEW QUESTION # 81
During EDA, a data scientist wants to look for patterns, such as linearity, in the data. Which of the following plots should the data scientist use?

  • A. Scatter
  • B. Violin
  • C. Box-and-whisker
  • D. Q-Q

Answer: A

Explanation:
# Scatter plots are used to examine relationships and trends between two numeric variables. They are especially effective at revealing linear (or nonlinear) patterns, clusters, and outliers.
Why the other options are incorrect:
* A: Violin plots show distribution and density, not relationships.
* B: Box plots compare distributions across groups but don't reveal linearity.
* D: Q-Q plots test normality, not variable relationships.
Official References:
* CompTIA DataX (DY0-001) Official Study Guide - Section 1.2:"Scatter plots are commonly used during EDA to identify correlations, linearity, and outliers between two continuous variables."
* Data Science Fundamentals, Chapter 2 - EDA Techniques:"To assess linear trends and relationships, scatter plots provide a direct visual assessment between variables."


NEW QUESTION # 82
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