希望alink 加入 层次聚类(hierarchical cluster)的功能实现
Open
- Dominant language
- Java
- Stars
- 3.6k
- Forks
- 780
- PR merge metrics
- No merged PRs in 30d
Description
希望alink 加入 层次聚类的功能实现 .
主要是 凝聚的层次聚类算法: 最小距离,平均距离,最大距离的层次聚类.
层次聚类方法在某些数据挖掘场景中可能是比 k-means更通用和有效的聚类方法, 希望社区有人可以加入此方法的实现, 或者提出相关计划..
Contributor guide
No contributing guide indexed for this repository
Research direction
The issue names no files, tests, or entry points. Start by locating Alink's existing k-means and clustering components, then review how their tests are organized; done means implementing agglomerative hierarchical clustering with minimum-, average-, and maximum-distance options.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- java
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 25/100