Answered: 1. The sum of squared distances between…

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

Concept explainers

Question

1. The sum of squared distances between projected data points and the origin is considered as

Group of answer choices

a) Eigenvalue

b) Eigenvector

c) Euclidean vector

d) Euclidean distance

2. Which of the following is a vector that does not get knocked off its span after transformation?

Group of answer choices

a) Eigenvector

b) Zero Vector

c) Unit Vector

d) Position Vector

e) All of the above

3. Which of the following is the most accurate clustering model?

Group of answer choices

a) Agglomerative hierarchical

b) Divisive hierarchical

c) k-Means

d) Depends on dataset

4. In unsupervised learning, the machine learns by which of the following?

Group of answer choices

a) Identifying patterns in the dataset

b) Using class labels

c) None of these

d) Both of these

5. An optimum number of clusters in agglomerative HC is found using which of the following?

Group of answer choices

a) Elbow Method

b) Random State

c) Dendrogram

d) None of these

Expert Solution

Step 1

Introduction

A clustering model is a type of machine learning algorithm that groups data points together into clusters based on similarity. Clustering algorithms are unsupervised, meaning they do not require labels or classes to be assigned to the data points. Clustering models can be used for a wide range of purposes, such as market segmentation, anomaly detection, and recommendation systems. Clustering algorithms are divided into two categories - hierarchical and partitioning. Hierarchical algorithms use a bottom-up approach to build clusters, while partitioning algorithms use a top-down approach. Clustering is a powerful tool for data analysis, as it allows for the discovery of hidden patterns and relationships in data sets.

Trending now

This is a popular solution!

Step by step

Solved in 3 steps

SEE SOLUTION Check out a sample Q&A here

Knowledge Booster

Learn more about

Need a deep-dive on the concept behind this application? Look no further. Learn more about this topic, computer-science and related others by exploring similar questions and additional content below.

Similar questions