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Hierarchical Clustering in Data Analysis

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Hierarchical Clustering in Data Analysis

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Questions and Answers

Hierarchical clustering is a type of _______ technique.

Dimensionality reduction

Regression

Classification

Clustering (correct)

What is the main goal of hierarchical clustering?

To identify the optimal number of clusters

To group similar objects into clusters (correct)

To reduce the dimensionality of a dataset

To predict a continuous output variable

Which of the following is NOT a characteristic of hierarchical clustering?

It can handle high-dimensional data

It produces a dendrogram

It assigns labels to each cluster

It is a supervised learning technique (correct)

What is the typical output of hierarchical clustering?

A dendrogram (A) Signup and view all the answers

What is the advantage of using hierarchical clustering over k-means clustering?

It does not require specifying the number of clusters (A) Signup and view all the answers

What is the primary objective of the least squares method in calculating the line of best fit?

To minimize the sum of the squares of the errors (C) Signup and view all the answers

Which of the following is NOT a characteristic of the least squares method?

It minimizes the mean of the data set (A) Signup and view all the answers

What is the consequence of using the least squares method on a dataset with outliers?

The line of best fit will be less accurate (C) Signup and view all the answers

Why is the least squares method commonly used in regression analysis?

Because it minimizes the sum of the squares of the errors (D) Signup and view all the answers

What is the advantage of using the least squares method over the mean absolute deviation method?

It provides a more accurate fit (B) Signup and view all the answers

Study Notes

Calculating the Line of Best Fit using the Least Squares Method

The line of best fit is calculated using the least squares method by minimizing the sum of the squares of the errors between the data points and the line of best fit.
This method is represented by option c.
The other options are incorrect:
- a. Minimizing the mean of the data set is not a criterion for the least squares method.
- b. Minimizing the sum of the absolute values of the errors is a different method, known as the least absolute deviations method.
- d. Minimizing the variance of the data set is not a direct method for calculating the line of best fit.

Hierarchical Clustering

Hierarchical clustering is a type of clustering technique.

Least Squares Method

The line of best fit is calculated using the least squares method by minimizing the sum of the squares of the errors between the data points and the line of best fit.

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Description

This quiz question asks about the type of technique that hierarchical clustering belongs to. It's a fundamental concept in data analysis and machine learning.