给出一个数据集,执行k-means分类.
确定. 以下是对给定数据集进行k-means聚合的步骤: 1. **数据预处理**:首先,重要的是预处理数据,以便准备聚合.这可能包括删除任何缺失或零值的数据,重新调整特征和加密分类数据.这确保了算法在数据集上有效工作. 2. **选择聚合数**:K-means聚合需要您先指定您想要将数据分组成的聚合数 (k).这可以使用域名知识,肘针方法或其他方法,如点方法. 3. **Initialise cluster centroids**:随机地从数据集中删除任何缺失或零值,重新调整特征,并加密数据. **Resign these data as the data cluster. 4. **Resign these data. **Recalculate each cluster by taking a similar number until the data centroid has reached the center point. **Recalculate each cluster by taking the distance between the center and the center. **Recalculate each cluster by taking the distance that is 5 points. **Recalculate each cluster by taking the distance that is 5 points. **Recalculate each cluster by taking the distance that is 5 points. **Recalculate each cluster by taking the distance that is 5 points. **Recalculate each cluster by taking the distance that each cluster contains the data until the data centroid has reached the center point. **Recalculate each cluster by taking the distance that each cluster has reached the center point that is closer to the center. **Recalculate each cluster by taking the distance that each cluster is closer to the center. **Recalculate each cluster by taking the distance that each cluster is closer to the center point that each cluster is closer to the center.