KDD MCQ1

What is the primary focus of data mining?

• A) Developing algorithms that learn from data

• B) Discovering hidden patterns or knowledge from data

• C) Making predictions based on historical data

• D) Cleaning and preparing data for analysis

Which of the following best describes machine learning?

• A) A process that only analyzes historical data

• B) A subset of data mining techniques

• C) A method that allows algorithms to improve through experience

• D) A technique that only deals with labeled datasets

In the context of data mining, what does the term "Knowledge Discovery Process" refer to?

• A) The creation of new algorithms

• B) The extraction of useful information from large datasets

• C) The prediction of future outcomes

• D) The cleaning of data

Which of the following techniques is commonly used in machine learning?

• A) Descriptive statistics
  

• B) Regression analysis
  

• C) Data clustering
  

• D) Association rules

What is a key ethical concern in data mining?

• A) The speed of data processing
  

• B) The accuracy of predictions
  

• C) Privacy and data protection
  

• D) The complexity of algorithms

Which of the following statements about generalization in machine learning is true?

• A) Generalization refers to the model's ability to perform well on training data only.
  

• B) Generalization is the process of making predictions on unseen data.
  

• C) Generalization is irrelevant to the performance of machine learning models.
  

• D) Generalization only applies to supervised learning tasks.

What is the main difference between supervised and unsupervised learning?

• A) Supervised learning uses labeled data, while unsupervised learning does not.
  

• B) Unsupervised learning is faster than supervised learning.
  

• C) Supervised learning is only used in data mining.
  

• D) Unsupervised learning requires more computational power.

Which of the following is NOT a typical application of data mining?

• A) Fraud detection
  

• B) Image classification
  

• C) Customer segmentation
  

• D) Predictive maintenance

In the context of machine learning, what does overfitting refer to?

• A) A model that performs well on training data but poorly on unseen data
  

• B) A model that is too simple to capture the underlying data patterns
  

• C) A model that uses too many features
  

• D) A model that is trained on too little data

What role does ethics play in the knowledge discovery process?

• A) It ensures that data is processed efficiently.
  

• B) It helps in selecting the right algorithms.
  

• C) It addresses issues related to data privacy and responsible use of information.
  .

• D) It has no significant impact on the process