Dendrogram visualization in SciPy - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is a dendrogram in data science?

A dendrogram is a tree-like diagram that shows how data points group together in hierarchical clustering. It helps us see the order and distance of clusters.

beginner

Which Python library provides the dendrogram function for hierarchical clustering visualization?

The scipy.cluster.hierarchy module provides the dendrogram() function to create dendrogram visualizations.

intermediate

What input does the dendrogram function require?

It requires a linkage matrix, which encodes the hierarchical clustering information such as which clusters are merged and their distances.

intermediate

How can you interpret the height of the branches in a dendrogram?

The height of each branch shows the distance or dissimilarity between clusters when they merge. Taller branches mean clusters are more different.

intermediate

Name one way to customize a dendrogram plot in scipy.

You can customize colors, orientation, labels, and truncate the dendrogram to show only a part of the tree using parameters like color_threshold, orientation, and truncate_mode.

What does a dendrogram visualize?

A Linear regression results

B Hierarchical clustering of data points

C Time series trends

D Classification accuracy

A dendrogram shows the hierarchical clustering structure of data.

Which function creates a dendrogram in scipy?

A scipy.cluster.hierarchy.distance()

B scipy.cluster.hierarchy.linkage()

C scipy.cluster.hierarchy.fcluster()

D scipy.cluster.hierarchy.dendrogram()

The dendrogram() function plots the hierarchical clustering as a tree.

What does the height of a dendrogram branch represent?

A Distance between merged clusters

B Cluster label

C Time taken to cluster

D Number of data points in cluster

Branch height shows how far apart clusters are when merged.

What input is needed to plot a dendrogram?

A Cluster labels

B Raw data points

C Linkage matrix

D Distance matrix

The linkage matrix contains the hierarchical clustering info needed.

Which parameter controls the orientation of a dendrogram plot?

A orientation

B truncate_mode

C color_threshold

D leaf_rotation

The orientation parameter sets the dendrogram direction (top, left, right, bottom).

Explain how a dendrogram helps in understanding hierarchical clustering results.

Think about how the tree shows groups joining step by step.

Describe the steps to create a dendrogram plot using scipy.

Start from data, then cluster, then plot.