1. What is the first step in the knowledge discovery process?
a) Data Mining
b) Data Cleaning
c) Data Selection
d) Data Transformation
Answer: b) Data Cleaning
2. Which of the following best describes data mining?
a) Collecting raw data from various sources
b) Identifying useful patterns and knowledge from data
c) Storing data for future use
d) Transforming data into a usable format
Answer: b) Identifying useful patterns and knowledge from data
3. What is the purpose of data preprocessing in the knowledge discovery process?
a) To remove errors and inconsistencies in data
b) To visualize patterns in data
c) To train machine learning models
d) To store data efficiently
Answer: a) To remove errors and inconsistencies in data
4. Which of the following is NOT a step in the knowledge discovery process?
a) Data Cleaning
b) Data Integration
c) Feature Engineering
d) Software Debugging
Answer: d) Software Debugging
5. What is the final stage of the knowledge discovery process?
a) Pattern Evaluation
b) Data Visualization
c) Knowledge Presentation
d) Data Cleaning
Answer: c) Knowledge Presentation
6. Which of these is an example of unsupervised learning in the context of knowledge discovery?
a) Regression analysis
b) Clustering
c) Classification
d) Time series analysis
Answer: b) Clustering
7. In knowledge discovery, what is the role of feature selection?
a) To reduce the dimensionality of data by selecting the most relevant features
b) To evaluate the performance of a predictive model
c) To store data for analysis
d) To clean noisy data
Answer: a) To reduce the dimensionality of data by selecting the most relevant features
8. What is the output of the data mining step in the knowledge discovery process?
a) Cleaned data
b) Data visualization
c) Discovered patterns or models
d) Raw data
Answer: c) Discovered patterns or models
9. What is the difference between data warehousing and data mining in knowledge discovery?
a) Data warehousing stores data, while data mining analyzes it.
b) Data warehousing cleans data, while data mining integrates it.
c) Data warehousing visualizes data, while data mining preprocesses it.
d) Data warehousing creates models, while data mining retrieves raw data.
Answer: a) Data warehousing stores data, while data mining analyzes it.
10. Which of the following evaluation methods is commonly used to assess the effectiveness of a discovered pattern?
a) Cross-validation
b) Data integration
c) Data cleaning
d) Data visualization
Answer: a) Cross-validation