What are the Challenges in Using Clustering Algorithms?
While clustering algorithms offer numerous benefits, they also present several challenges:
1. Choosing the Right Number of Clusters: Determining the optimal number of clusters (k) can be difficult and often requires domain knowledge and experimentation. 2. Scalability: Handling large datasets can be computationally expensive and time-consuming. 3. Interpretability: The results of clustering algorithms can sometimes be hard to interpret, making it challenging to derive actionable insights. 4. Data Quality: Poor-quality data can lead to unreliable clusters, highlighting the importance of robust data preprocessing.