Brute force kNN search (based on cosine similarity) select t1. rowid , cosine_similarity(t1.features, q1.features) as similarity -- hive v0.3.2 or later -- cosine_similarity(t1.features, q1.features, false) as similarity -- hive v0.3.1 or before from news20mc_train t1 CROSS JOIN ( select features from news20mc_test where rowid = 1 ) q1 ORDER BY ... KNN is unsupervised, Decision Tree (DT) supervised. (KNN is supervised learning while K-means is unsupervised, I think this answer causes some confusion.) KNN is used for clustering, DT for classification. (Both are used for classification.) KNN determines neighborhoods, so there must be a distance metric.
Dec 27, 2020 · Train and test the Bagging classifier using the training and test sets generated based on the method tried as part of the 2 nd Task. 4 th Task: Build Train and Test a Stacking type Classifier . You need to construct, train and test a Stacking type classifier in R, based on (CART, KNN, NB).