In k-means clustering, k represents the

In K-Means clustering, the number of clusters, k, must be specified in advance.

In K-Means clustering, the number of clusters, k, must be specified in advance.Group of answer choicesTrueFalse

What does K stand for in K mean algorithm?(1 Point)Number of clustersNumber of dataNumber of attributesNumber of iterations

Which function in scikit-learn is used to perform K-Means clustering?Answer areaK Means Cluster ()K Means ()K Means Clustering ()Cluster K Means ()

Suppose you have a dataset of customer transactions from an online retail store. Each data point represents a customer and contains two features: "Total Amount Spent" (in pounds) and "Total Number of Items Purchased." You want to divide the customers into different groups based on their spending behaviour.Which of the following statements about K-means clustering applied to this dataset is true?Group of answer choicesThe number of clusters (K) is determined by the mean of "Total Amount Spent" and "Total Number of Items Purchased."K-means is sensitive to the initial placement of cluster centres, so it's essential to initialise them randomly.K-means will always produce the same clustering result, regardless of the initial positions of the cluster centres.K-means is not suitable for clustering real-valued data and can only handle categorical features.