The correct answer is D. To classify data points based on the majority class among their K nearest neighbors.
K-nearest neighbors (K-NN) is a supervised machine learning algorithm that can be used for both classification and regression tasks. It is a simple algorithm that works by finding the K nearest neighbors of a given data point and then assigning the data point to the class that is most common among its neighbors.
K-NN is a non-parametric algorithm, which means that it does not make any assumptions about the underlying distribution of the data. This makes it a versatile algorithm that can be applied to a wide variety of problems.
K-NN is also a relatively simple algorithm to implement. It does not require any feature extraction or dimensionality reduction, and it can be easily parallelized.
However, K-NN can be computationally expensive, especially for large datasets. It can also be sensitive to the choice of K, which is a hyperparameter that needs to be tuned for each problem.
Overall, K-NN is a simple, versatile, and effective machine learning algorithm that can be used for both classification and regression tasks. It is particularly well-suited for problems where the data is not well-represented by a parametric model.
Here is a brief explanation of each option:
- A. To perform regression analysis: Regression analysis is a statistical method that is used to model the relationship between two or more variables. K-NN is not a regression algorithm, so it cannot be used to perform regression analysis.
- B. To cluster data into groups: Clustering is a data mining task that involves grouping data points together based on their similarity. K-NN can be used for clustering, but it is not a clustering algorithm.
- C. To reduce dimensionality: Dimensionality reduction is a data preprocessing technique that is used to reduce the number of dimensions in a dataset. K-NN is not a dimensionality reduction algorithm.
- D. To classify data points based on the majority class among their K nearest neighbors: This is the main purpose of the K-nearest neighbors (K-NN) algorithm in machine learning.