Learn how to use Weka for clustering tasks.
- [Instructor] Clustering is another very popular…machine learning or ML task.…Unlike classification,…it belongs to unsupervised learning.…Let's find out how Weka handles this very common task…of clustering in data science.…The first step is loading our dataset.…We'll be using the iris dataset provided by Weka by default.…This is a famous dataset that contains morphologic variation…of iris flowers of three related species.…
Since there are three different species involved here,…my hope is that our clustering ML can detect…the three groups as expected.…Now that I've loaded the data, let's move forward.…Choose the Cluster tab next.…Click choose.…Here you see several well known clustering algorithms.…Pick SimpleKMeans.…You can adjust the properties of the clustering algorithm…of your choice by clicking on its name here.…
We can guide our clustering algorithm a little more…by giving the number of clusters.…Since we know the number will most probably be three,…let's put three here and click OK.…Now we are ready to run our clustering algorithm.…
- Enabling technologies in data science
- Cloud computing and virtualization
- Installing and working with Proxmox, Hadoop, Spark, and Weka
- Managing virtual machines on Proxmox
- Distributed processing with Spark
- Fundamental applications of machine learning
- Distributed systems and distributed processing
- How Hadoop, Spark, and Weka can work together
Skill Level Beginner
Course organization1m 17s
1. Introduction to Data Science
2. Cloud Computing
3. Distributed File Systems
4. Distributed Processing
5. Machine Learning
6. Case Study
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