K-Means is a type of hierarchical clusteringTrueFalse

Answered: K-Means is a type of hierarchical…

Engineering

Computer Science

K-Means is a type of hierarchical clustering True O False

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

See similar textbooks

Related questions

Q: Assume there is a class named Car with an attribute named model of type string an ype Car already…

A: Given data: Car is the name of the class. It contains an attribute model of type String. It contains…

Q: es of complexity. 1. Arrays 2. Graphs Hash Tables 3.

A: Disadvantages of array are:• The size of array must be declared before its use • Running time can…

Q: # 7. What is the K-means clustering method?

A: K-means is a popular unsupervised machine learning algorithm used for clustering data points into…

Q: How is KNN different from k-means clustering?

A: INTRODUCTION: K-means : K-means Clustering is a vector quantization approach derived from signal…

Q: K-means clustering is run on some data, for a few different values of K. Shown is the plot obtained…

A: To determine the natural number of clusters to use, look for the "elbow point" in the inertia plot.…

Q: What is a coding example of a Singly Linked search?

A: Searching is performed in order to find the location of a particular element in the list. Searching…

Q: What is clustering and how does it work? Describe any two types of clustering algorithms in a few…

A: Clustering, also known as cluster analysis, is a machine learning algorithm that groups unlabeled…

Q: Double hashing is used to overcome primary clustering. True O False

A: Double hashing should be uniform hashing.

Q: For hard clustering algorithms such as K-Mean, each instance can be in more than one clusters. Is…

A: In this type of clustering algorithm each data item has been grouped together such that each item is…

Q: What difference does clustering (k-means) with and without normalisation make?

A: Introduction: K-means clustering is a vector quantization method for dividing n observations into k…

Q: Why and how do local minima affect k-means clustering? What are our options for dealing with…

A: Introduction: Various initializations may generate different clusters due to the iterative nature of…

Q: What are the differences between the k-means clustering algorithms used by Tableau and RapidMiner…

A: K-means clustering techniques are available for data analysis in two well-known data analytics…

Q: Describe step by step process of bisecting k-means clustering.

A: step by step process of bisecting k-means clustering algortihm.

Q: come between Hierarchical and K-Me

A: Below the differences in the outcome between Hierarchical and K-Means Cluster methods

Q: In data structures and algorithms,the worst case efficiency of binary search is

A: Binary Search is a searching algorithm where particular element is searched in an entire array If…

Q: Hierarchical clustering works by starting with a matrix and initial points as clusters and then…

A: A Hierarchical clustering method works by grouping data into a tree of clusters. Hierarchical…

Q: Describe K-Means Clustering Algorithm and Hierarchy Cluster Algorithm including principles and…

A: Describe K-Means Clustering Algorithm K-Means Clustering is an unsupervised learning algorithm that…

Q: What is systematic sampling and cluster sampling?

A: The way sample points are obtained from the sample population varies between systematic sampling and…

Q: Explain how random forest is used for similarity measure.

A: A random forest is a machine learning technique for solving classification and regression problems.…

Q: How does query optimization differ when querying against nested JSON objects as compared to flat…

A: Query optimization strategies can differ significantly when querying against nested JSON objects…

Q: Algorithm to Relational k-Means Clustering Input: T1, T4, number of clusters k, and number of…

A: Below is the complete solution with explanation in detail for the given question about Relational…

Q: Discuss how K-MEANS clustering work

A: K means clustering: K-Means is a clustering technique that aims to identify groups in data. ‘K’ is…

Q: coordinates and names of all surrounding dining establishments. The only questions that need…

A: In this scenario, we have access to a database that contains the x, y coordinates and names of all…

Q: What is the significance of clustering (k-means) with and without normalization?

A: k-means clustering is a vector quantization approach that tries to split n observations into k…

Q: Write Algorithm for Relational k-Means Clustering

A: Here is an outline for an algorithm for relational k-means clustering: Initialize the number…

Q: ther are there in a chaining hash table of size T? The Separate Chaining hash table uses what types…

A: Introduction: In this particular inquiry, we wanted to know how many linked lists are included…

Q: Q: Why and how are local minima a problem for k-means clustering? How do we deal with these?

A: Answer: Because of the iterative nature of kmeans and the random initialization of centroids at the…

Q: Clustering Input: T1, T4, number of clusters k, and number of iterations

A: Dear Student, The answer to your question is given below -

Q: What's the difference between classification and clustering?

A: Introduction: Machine Learning Algorithms: In general, machine learning algorithms use unsupervised…

Q: ९९

A: The first one (top left) is a random classifier and hence is not able to derive class boundaries.…

Q: Does HTML have any tricks up its sleeve that set it apart from the rest of the pack?

A: HTML (Hypertext Markup Language) is a foundational language used for creating and structuring web…

Q: Below dissimilarity between four data objects are given. If complete link inter-clustering distance…

A: The solution for the above given question is given below:

Q: How can you select K for K-means Clustering?

A: solution:-

Q: Please provide an explanation of the two most significant benefits that come from using binary…

A: Introduction: In point of fact, BST is an abbreviation for "Binary Search Tree." It is sometimes…

Question

K-Means is a type of hierarchical clustering
True
False

Expert Solution

Step 1

K- Means:-

To discover groupings that haven't been explicitly identified in the data, the K-means clustering method is employed. This may be used to verify business assumptions about the sorts of groups that exist, as well as to find unknown groups in large data sets.

Step by step

Solved in 2 steps

SEE SOLUTION Check out a sample Q&A here

Similar questions

Defintion of roundoff mistake
True or False: Clustering refers to a broad set of techniques for finding subgroups or clusters in a data set.
Discuss the hash table data structure and its relevance to the implementation of dictionaries in Python.
What are the differences between how RapidMiner (RM) and Tableau execute k-means clustering?
Subject: Machine Learning Apply single-link and complete-link hierarchical clustering method to construct two different dendrograms. Using the two dendrograms find the number of clusters at distance 8 [Hint: cut the dendrogram at distance 8].
What Is pseudodirect?
Differentiate between k-means and k-median clustering algorithm.
Highlight strengths and weaknesses of k-means clustering algorithm.
What Is K-Means Clustering?
2)What is K- means Algorithm? Describe the use of it with a math example? 3) What is Fuzzy c-means clustering? Describe the use of it with a math example? 4)What is QT clustering algorithm ? Describe the use of it with a math example?