Can you use KNN for categorical variables?
Table of Contents
- 1 Can you use KNN for categorical variables?
- 2 Which distance measures can be used for categorical attributes?
- 3 How do you choose metric distance in KNN?
- 4 What is most widely used distance metric in k-NN?
- 5 Which distance measure is mostly used for numeric attributes in k-NN classifier?
- 6 What is most widely used distance metric in Knn?
Can you use KNN for categorical variables?
KNN is an algorithm that is useful for matching a point with its closest k neighbors in a multi-dimensional space. It can be used for data that are continuous, discrete, ordinal and categorical which makes it particularly useful for dealing with all kind of missing data.
Which distance measures can be used for categorical attributes?
Many fuzzy clustering algorithms have been developed for categorical datasets. However, in most of these methods Hamming distance is used to define the distance between the two categorical feature values.
How do you choose metric distance in KNN?
There are many kinds of distance functions that can be used in KNN such as Euclidean Distance, Hamming distance, Minkowski distance, Kullback-Leiber (KL) divergence, BM25 etc.
What is most widely used distance metric in KNN Mcq?
Euclidean Distance – This distance is the most widely used one as it is the default metric that SKlearn library of Python uses for K-Nearest Neighbour. It is a measure of the true straight line distance between two points in Euclidean space.
What distance is used for categorical variables?
a) preferably use Cosine distance if there are a large number of variables (.. say >8). Matching and Jaccard’s coefficient: Matching and Jaccard’s coefficients are close in derivations, used to measure when categorical variables are present in the data.
What is most widely used distance metric in k-NN?
Since the Euclidean distance function is the most widely used distance metric in k-NN, no study examines the classification performance of k-NN by different distance functions, especially for various medical domain problems.
Which distance measure is mostly used for numeric attributes in k-NN classifier?
ED is the most widely used distance metric in KNN classifications; however, only few studies examined the effect of different distance metrics on the performance of KNN, these used a small number of distances, a small number of data sets, or both.