Question: What is the term for the process of reducing the dimensionality of data while preserving its essential features?
Answer:
Dimensionality reduction is the process of reducing the dimensionality of data while preserving its essential features.
MCQ: What is the term for the process of reducing the dimensionality of data while preserving its essential features?
Correct Answer:
A. Clustering
Explanation:
Dimensionality reduction is the process of reducing the dimensionality of data while preserving its essential features.
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Related Questions
- 1. What type of machine learning algorithm is used for predicting numerical values or continuous outcomes?
- 2. Which machine learning technique aims to find the optimal solution by mimicking the process of natural selection and evolution?
- 3. In machine learning, what is the primary goal of feature engineering?
- 4. What is the term for the process of converting text data into numerical values for machine learning?
- 5. Which machine learning algorithm is commonly used for sentiment analysis in natural language processing (NLP)?
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