When we consider clustering techniques, which of the following apply: (select ALL answers that are correct, there may be more than 1) ☐ The k-means++ algorithm chooses only one of the centroids completely randomly ☐ The optimal value of k is selected based on the highest observed accuracy The goal in k-means is to minimize variance within clusters We cluster using the training data and then validate the clusters with the testing data We must have a target variable in the data that specifies the cluster labels The k-means (or k-means++) algorithm selects the optimal value of k when it performs clustering
When we consider clustering techniques, which of the following apply: (select ALL answers that are correct, there may be more than 1) ☐ The k-means++ algorithm chooses only one of the centroids completely randomly ☐ The optimal value of k is selected based on the highest observed accuracy The goal in k-means is to minimize variance within clusters We cluster using the training data and then validate the clusters with the testing data We must have a target variable in the data that specifies the cluster labels The k-means (or k-means++) algorithm selects the optimal value of k when it performs clustering
Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
Problem 1PE
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k-means question from scikit-learn. Thank you.
Transcribed Image Text:When we consider clustering techniques, which of the following apply: (select ALL answers that
are correct, there may be more than 1)
The k-means++ algorithm chooses only one of the centroids completely randomly
The optimal value of k is selected based on the highest observed accuracy
The goal in k-means is to minimize variance within clusters
We cluster using the training data and then validate the clusters with the testing data
We must have a target variable in the data that specifies the cluster labels
The k-means (or k-means++) algorithm selects the optimal value of k when it performs
clustering
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