Question 1(True/False) An advantage of k nearest neighbor methods is that they can leverage categorical data without encoding.1 pointTrueFalse

Answer:

The statement is True.

Explanation:

The k-nearest neighbors (k-NN) algorithm can indeed handle categorical data without the need for one-hot encoding or other forms of numerical transformation. This is because k-NN operates on distance metrics, and can use measures like Hamming distance for categorical variables, which simply counts the number of mismatches between categorical values. This characteristic makes k-NN versatile in scenarios with both categorical and numerical datasets, allowing for a direct application to various types of data without additional preprocessing steps that are usually required for other machine learning algorithms.