See test scores and detailed information for Timberwood Middle School in Humble, TX 77346. This Texas school is located at 18450 Timber Forest Drive and is in the Humble Independent School District Saved Homes
K-Means Advantages : 1) If variables are huge, then K-Means most of the times computationally faster than hierarchical clustering, if we keep k smalls. 2) K-Means produce tighter clusters than hierarchical clustering, especially if the clusters are globular.K-Means Disadvantages : 1) Difficult to predict K-Value.2) With global cluster, it didn't work well.) K-Means produce tighter clusters than hierarchical clustering, especially if the clusters are globular. K-Means Disadvantages : 1) Difficult to predict K-Value. 2) With global cluster, it didn't work well.
Next: Hierarchical Classifiers Up: classification Previous: Some special cases Unsupervised Classification - Clustering. A clustering algorithm groups the given samples, each represented as a vector in the N-dimensional feature space, into a set of clusters according to their spatial distribution in the N-D space. Clustering is an unsupervised classification as no a priori knowledge (such as samples of known classes) is assumed to be available. The K-Means Algorithm. Step 1. Randomly choose initial cluster centers from the given sample set (e.g., the first samples of the sample set). Set ; Step 2.