- Import necessary libraries.
- Preprocess the data: Standardized the features to ensure equal contribution.
- Determine the optimal number of clusters using the Elbow method: The Elbow graph indicated 3 as the optimal number.
- Apply KMeans clustering: Clustered the data into 3 clusters.
- Visualize the clusters: Created a scatter plot to visually represent the clusters.
-
Notifications
You must be signed in to change notification settings - Fork 0
The dataset includes the following columns: Id, SepalLengthCm, SepalWidthCm, PetalLengthCm, PetalWidthCm, and Species. We will use the Sepal and Petal measurements to predict the optimum number of clusters using the KMeans algorithm.
sajjad425/kmeans_clustering
Folders and files
| Name | Name | Last commit message | Last commit date | |
|---|---|---|---|---|
Repository files navigation
About
The dataset includes the following columns: Id, SepalLengthCm, SepalWidthCm, PetalLengthCm, PetalWidthCm, and Species. We will use the Sepal and Petal measurements to predict the optimum number of clusters using the KMeans algorithm.
Topics
Resources
Stars
Watchers
Forks
Releases
No releases published
Packages 0
No packages published