Cluster Analysis
(การวิเคราะห์กลุ่ม)
Definition
Cluster Analysis (การวิเคราะห์กลุ่ม) Hard Skill
Cluster Analysis is a statistical technique used to group sets of objects in such a way that objects in the same group are more similar to each other than to those in other groups. It is commonly used for data segmentation, pattern recognition, and exploratory data analysis.
Expertise Level
Level 1
Basic
1. Understands the fundamental concept of grouping data based on similarity.
2. Can describe basic clustering methods such as K-means or hierarchical clustering.
3. Able to interpret simple cluster outputs from software tools.
Level 2
Intermediate
1. Can apply appropriate clustering algorithms to various datasets.
2. Understands how to select features and preprocess data for effective clustering.
3. Able to evaluate cluster quality using metrics like silhouette score or Davies-Bouldin index.
Level 3
Advanced
1. Can design and implement advanced cluster analysis workflows for complex datasets.
2. Integrates cluster analysis with other modeling techniques for deeper insights.
3. Able to debug and optimize clustering algorithms and interpret multidimensional cluster structures.
