Python for Data Science and Machine Learning
Python for Data Science and Machine Learning - Important Points
| 21. | Which of the following is a data preprocessing technique in machine learning? |
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A. Standardization
B. PCA
C. K-means clustering
D. Gradient descent
View Answer Discuss Work SpaceAnswer: option a
Explanation:
Standardization is a data preprocessing technique used in machine learning to scale the data to a common range, in order to improve the performance of the model.
| 22. | Which of the following is a classification algorithm in machine learning? |
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A. Linear regression
B. K-nearest neighbors
C. Gradient descent
D. None of the above
View Answer Discuss Work SpaceAnswer: option b
Explanation:
K-nearest neighbors is a classification algorithm in machine learning, which assigns a class to a new data point based on the majority class of its k-nearest neighbors in the training data.
| 23. | Which of the following is a regression algorithm in machine learning? |
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A. K-means clustering
B. Decision tree
C. Random forest
D. Linear regression
View Answer Discuss Work SpaceAnswer: option d
Explanation:
Linear regression is a regression algorithm in machine learning, which models the relationship between a dependent variable and one or more independent variables.
| 24. | Which of the following is a method for reducing dimensionality in machine learning? |
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A. PCA
B. K-means clustering
C. Gradient descent
D. None of the above
View Answer Discuss Work SpaceAnswer: option a
Explanation:
PCA (Principal Component Analysis) is a method for reducing dimensionality in machine learning, by transforming the data into a lower-dimensional space while retaining most of the variability in the data.
| 25. | Which of the following is a Python library for visualization in machine learning? |
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A. NumPy
B. Pandas
C. Seaborn
D. Scikit-learn
View Answer Discuss Work SpaceAnswer: option c
Explanation:
Seaborn is a Python library for visualization in machine learning, providing high-level interface for creating statistical graphics.