Cluster2A is made and published by Chu-Yi Chang. AppBrain is an independent app data site and isn't affiliated with Chu-Yi Chang. The app name, icon, screenshots and description belong to Chu-Yi Chang and are shown as published on the App Store.
AppBrain's verdict
- Last updated
- February 22, 2026
Rankings
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Releases
Updates seen on the App Store- Version
- 26.0
- Launched
- December 2020
No changelog data
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Technology
Found in the app by AppBrain- Price
- Free
- App size
- 8.86 MB
- Content rating
- Everyone
Technologies used by Cluster2A
About the app and developer
About Cluster2A
Cluster2A is a productivity app developed by Chu-Yi Chang.
User Ratings
The app has no ratings yet.
App Information
Cluster2A is freely available from the App Store. The app size is 8.86 MB. The latest version available is 26.0. The last update was on February 22, 2026.
Technical Requirements
The app has a content rating of Everyone. The app has been available on the App Store since December 2020.
Developer information for Chu-Yi Chang
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Frequently asked questions about Cluster2A
Is Cluster2A free?
Yes. Cluster2A is free on the App Store.
Is Cluster2A still available?
Yes. Cluster2A is on the App Store, and the last update we saw was on February 22, 2026.
How large is Cluster2A?
Cluster2A is 8.86 MB.
Is Cluster2A suitable for children?
App Store rates the content of Cluster2A as suitable for everyone.
Who made Cluster2A?
Cluster2A was developed by Chu-Yi Chang. It is listed in the productivity category on the App Store.
What are the best alternatives to Cluster2A?
People looking at Cluster2A also look at these productivity apps: B&W Film Dev, Telerik .NET MAUI Controls, rubyi - run code, autocomplete, ivySCI, Random Notification.
Store listing
By Chu-Yi Chang, from the App Store
Description by Chu-Yi Chang Written by the developer, not by AppBrain. Click to read.
Common application scenarios:
Customer and market segmentation: Grouping customers based on their behavior, demographic characteristics, or purchase history for targeted marketing and personalized recommendations.
Retail analytics: Identifying "hotspot areas" in a store through cluster analysis of customer locations.
Cluster2A combines two machine learning algorithms, K-means and DBSCAN, to help users with small datasets take their first steps into the world of machine learning more easily and enjoyably.