APPLICATION OF SUPERVISED LEARNING
CLASSIFICATION IN MACHINE LEARNING
|
Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
|
|
|
Only for Classification
|
|
|
Only for Regression
|
|
|
Both Classification and Regression
|
|
|
None of the Mentioned
|
Detailed explanation-1: -Yes, we can use KNN for regression. Here, we take the k nearest values of the target variable and compute the mean of those values. Those k nearest values act like regressors of linear regression.
Detailed explanation-2: -The k-nearest neighbors algorithm, also known as KNN or k-NN, is a non-parametric, supervised learning classifier, which uses proximity to make classifications or predictions about the grouping of an individual data point.
Detailed explanation-3: -Yes, KNN can be used for regression problem statements. In other words, the KNN algorithm can be applied when the dependent variable is continuous. For regression problem statements, the predicted value is given by the average of the values of its k nearest neighbours.
Detailed explanation-4: -kNN stands for k Nearest Neighbor. In data mining and predictive modeling, it refers to a memory-based (or instance-based) algorithm for classification and regression problems. It is a widely used algorithm with many suc-cessfully applications in medical research, business applications, etc.