clustering and association in unsupervised machine learning

The unsupervised learning algorithm which aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest centroid is Hierarchical clustering K-means clustering KNN None of the above

What is the primary goal of clustering in machine learning?Answer areaPredicting continuous valuesClassifying data points into predefined categoriesGrouping similar data points togetherReducing the dimensionality of data

Question 4Which of the following is NOT an attribute of Unsupervised Learning?1 pointThe algorithm ingests unlabeled data, draws inferences, and finds patterns from unstructured dataIt is useful for clustering data, where data is grouped according to how similar it is to its neighbors and dissimilar to everything elseTakes data and rules as input and uses these inputs to develop an algorithm that will give us an answerIt is useful for finding hidden patterns and or groupings in data and can be used to differentiate normal behavior with outliers such as fraudulent activity

Which of the following is TRUE about unsupervised learning?I.  Unsupervised learning refers to the problem of finding hidden structures within unlabeled data.II.  Clustering techniques are unsupervised in the sense that the data scientist does not determine, in advance, the labels to apply to the clusters.II only neither I nor IIboth I and III only

In ___________, the data is grouped into clusters, where each cluster indicate something about categories and classes present in the data.a.non-parameterized unsupervised learningb.non-parameterized supervised learningc.parameterized unsupervised learningd.parameterized supervised learning