数据科学与大数据分析学习笔记-5聚类


聚类是指通过无监督(unsupervised)技术对相似的数据对象进行分组形成簇。

K-means Clustering

给定m个对象的集合每个对象都有n个可测量的属性。
分四步:

  1. Choose the value of k, and the k initial guess for the centroids
    选定 k 值,以及 k 个质心的初始猜测值。
  2. Compute the distance from each data point to each centroid. Assign each point to the closest centroid.
    计算从每个数据点(xi ,yi )到每个质心的距离,然后每个点分配给最近的质心。所有分配
    给同一个质心的点组成一个簇。一共形成 k 个簇,使用欧几里得距离来测量。
    在这里插入图片描述
  3. Update the centroid of each cluster to become the center of gravity of the cluster.
    算步骤 2 中新形成定义的每一个簇的质量中心,即新质心。
    在这里插入图片描述
    其中center of gravity是
Data Science and Big Data Analytics is about harnessing the power of data for new insights. The book covers the breadth of activities and methods and tools that Data Scientists use. The content focuses on concepts, principles and practical applications that are applicable to any industry and technology environment, and the learning is supported and explained with examples that you can replicate using open-source software. This book will help you: Become a contributor on a data science team Deploy a structured lifecycle approach to data analytics problems Apply appropriate analytic techniques and tools to analyzing big data Learn how to tell a compelling story with data to drive business action Prepare for EMC Proven Professional Data Science Certification Corresponding data sets are available at www.wiley.com/go/9781118876138. Get started discovering, analyzing, visualizing, and presenting data in a meaningful way today! Table of Contents Chapter 1 Introduction to Big Data Analytics Chapter 2 Data Analytics Lifecycle Chapter 3 Review of Basic Data Analytic Methods Using R Chapter 4 Advanced Analytical Theory and Methods: Clustering Chapter 5 Advanced Analytical Theory and Methods: Association Rules Chapter 6 Advanced Analytical Theory and Methods: Regression Chapter 7 Advanced Analytical Theory and Methods: Classification Chapter 8 Advanced Analytical Theory and Methods: Time Series Analysis Chapter 9 Advanced Analytical Theory and Methods: Text Analysis Chapter 10 Advanced Analytics—Technology and Tools: MapReduce and Hadoop Chapter 11 Advanced Analytics—Technology and Tools: In-Database Analytics Chapter 12 The Endgame, or Putting It All Together
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