# Clustering in Machine Learning

statistics-clustering_machinelearning/clustering

Author(s)

version Version
2
last_modification Last updated
Jul 23, 2020
None Specified, defaults to CC-BY-4.0
galaxy-tags Tags
statistics
clustering
ml

Features

Tutorial
hands_on Clustering in Machine Learning

Workflow Testing
Tests: ✅
Results: Not yet automated
FAIRness purl PURL
https://gxy.io/GTN:W00223
Launch in Tutorial Mode question
flowchart TD
0["ℹ️ Input Dataset\niris"];
style 0 stroke:#2c3143,stroke-width:4px;
1["ℹ️ Input Dataset\ncircles"];
style 1 stroke:#2c3143,stroke-width:4px;
10["Numeric Clustering"];
2 -->|output| 10;
11["Numeric Clustering"];
2 -->|output| 11;
12["Numeric Clustering"];
3 -->|tabular| 12;
13["Numeric Clustering"];
3 -->|tabular| 13;
14["Numeric Clustering"];
3 -->|tabular| 14;
15["Scatterplot with ggplot2"];
5 -->|outfile| 15;
275528af-4af3-4dc6-a958-737f4d2f89bd["Output\nheirarchical_clustering_circles"];
15 --> 275528af-4af3-4dc6-a958-737f4d2f89bd;
style 275528af-4af3-4dc6-a958-737f4d2f89bd stroke:#2c3143,stroke-width:4px;
16["Scatterplot with ggplot2"];
6 -->|outfile| 16;
870b03ca-6b2c-42ab-bbcc-6c4bbecf8ea9["Output\nkmeans_clustering_circles"];
16 --> 870b03ca-6b2c-42ab-bbcc-6c4bbecf8ea9;
style 870b03ca-6b2c-42ab-bbcc-6c4bbecf8ea9 stroke:#2c3143,stroke-width:4px;
17["Scatterplot with ggplot2"];
7 -->|outfile| 17;
9664ba05-4664-4ceb-8f93-0974b20bf9e1["Output\ndbscan_clustering_circles"];
17 --> 9664ba05-4664-4ceb-8f93-0974b20bf9e1;
style 9664ba05-4664-4ceb-8f93-0974b20bf9e1 stroke:#2c3143,stroke-width:4px;
18["Scatterplot with ggplot2"];
9 -->|outfile| 18;
d82a4483-7f38-4614-96b4-2a9b3316c808["Output\nheirarchical_clustering_moon"];
18 --> d82a4483-7f38-4614-96b4-2a9b3316c808;
style d82a4483-7f38-4614-96b4-2a9b3316c808 stroke:#2c3143,stroke-width:4px;
19["Scatterplot with ggplot2"];
10 -->|outfile| 19;
00c0ca58-4ee5-4606-8c1b-c172431e5dbd["Output\ndbscan_clustering_moon"];
19 --> 00c0ca58-4ee5-4606-8c1b-c172431e5dbd;
style 00c0ca58-4ee5-4606-8c1b-c172431e5dbd stroke:#2c3143,stroke-width:4px;
2["ℹ️ Input Dataset\nmoon"];
style 2 stroke:#2c3143,stroke-width:4px;
20["Scatterplot with ggplot2"];
11 -->|outfile| 20;
5717bf22-83e3-46a2-8f6d-12a1fa41439b["Output\nkmeans_clustering_moon"];
20 --> 5717bf22-83e3-46a2-8f6d-12a1fa41439b;
style 5717bf22-83e3-46a2-8f6d-12a1fa41439b stroke:#2c3143,stroke-width:4px;
21["Scatterplot with ggplot2"];
12 -->|outfile| 21;
0ace8714-ff3a-4efd-a649-70924b1e6230["Output\nheirarchical_clustering_iris"];
21 --> 0ace8714-ff3a-4efd-a649-70924b1e6230;
style 0ace8714-ff3a-4efd-a649-70924b1e6230 stroke:#2c3143,stroke-width:4px;
22["Scatterplot with ggplot2"];
13 -->|outfile| 22;
e6f69d7d-c9e3-4023-8daf-87f6b0afc3fd["Output\nkmeans_clustering_iris"];
22 --> e6f69d7d-c9e3-4023-8daf-87f6b0afc3fd;
style e6f69d7d-c9e3-4023-8daf-87f6b0afc3fd stroke:#2c3143,stroke-width:4px;
23["Scatterplot with ggplot2"];
14 -->|outfile| 23;
119d1cde-567a-47f0-99de-00d3557c38a2["Output\ndbscan_clustering_iris"];
23 --> 119d1cde-567a-47f0-99de-00d3557c38a2;
style 119d1cde-567a-47f0-99de-00d3557c38a2 stroke:#2c3143,stroke-width:4px;
3["Convert CSV to tabular"];
0 -->|output| 3;
4["Scatterplot with ggplot2"];
1 -->|output| 4;
5["Numeric Clustering"];
1 -->|output| 5;
6["Numeric Clustering"];
1 -->|output| 6;
7["Numeric Clustering"];
1 -->|output| 7;
8["Scatterplot with ggplot2"];
2 -->|output| 8;
9["Numeric Clustering"];
2 -->|output| 9;

## Inputs

Input Label
Input dataset iris
Input dataset circles
Input dataset moon

## Outputs

From Output Label
toolshed.g2.bx.psu.edu/repos/iuc/ggplot2_point/ggplot2_point/2.2.1+galaxy2 Scatterplot with ggplot2
toolshed.g2.bx.psu.edu/repos/iuc/ggplot2_point/ggplot2_point/2.2.1+galaxy2 Scatterplot with ggplot2
toolshed.g2.bx.psu.edu/repos/iuc/ggplot2_point/ggplot2_point/2.2.1+galaxy2 Scatterplot with ggplot2
toolshed.g2.bx.psu.edu/repos/iuc/ggplot2_point/ggplot2_point/2.2.1+galaxy2 Scatterplot with ggplot2
toolshed.g2.bx.psu.edu/repos/iuc/ggplot2_point/ggplot2_point/2.2.1+galaxy2 Scatterplot with ggplot2
toolshed.g2.bx.psu.edu/repos/iuc/ggplot2_point/ggplot2_point/2.2.1+galaxy2 Scatterplot with ggplot2
toolshed.g2.bx.psu.edu/repos/iuc/ggplot2_point/ggplot2_point/2.2.1+galaxy2 Scatterplot with ggplot2
toolshed.g2.bx.psu.edu/repos/iuc/ggplot2_point/ggplot2_point/2.2.1+galaxy2 Scatterplot with ggplot2
toolshed.g2.bx.psu.edu/repos/iuc/ggplot2_point/ggplot2_point/2.2.1+galaxy2 Scatterplot with ggplot2

## Tools

csv_to_tabular
toolshed.g2.bx.psu.edu/repos/bgruening/sklearn_numeric_clustering/sklearn_numeric_clustering/1.0.8.1 View in ToolShed
toolshed.g2.bx.psu.edu/repos/iuc/ggplot2_point/ggplot2_point/2.2.1+galaxy2 View in ToolShed

To use these workflows in Galaxy you can either click the links to download the workflows, or you can right-click and copy the link to the workflow which can be used in the Galaxy form to import workflows.

## Importing into Galaxy

Below are the instructions for importing these workflows directly into your Galaxy server of choice to start using them!
Hands-on: Importing a workflow
• Click on Workflow on the top menu bar of Galaxy. You will see a list of all your workflows.
• Click on galaxy-upload Import at the top-right of the screen
• Option 1: Paste the URL of the workflow into the box labelled “Archived Workflow URL”
• Option 2: Upload the workflow file in the box labelled “Archived Workflow File”
• Click the Import workflow button

Below is a short video demonstrating how to import a workflow from GitHub using this procedure: