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同济大学：《大数据分析与数据挖掘 Big Data Analysis and Mining》课程教学资源（PPT课件讲稿）Evaluation & other classifiers

◼ Cluster Basics ◼ Clustering algorithms  Hierarchical clustering  k-means  Expectation-Maximization (EM) ◼ Cluster Validity  determining the number of clusters  clustering evaluation

Data Objects and Attribute Types Basic Statistical Descriptions of Data Data Visualization Measuring Data Similarity and Dissimilarity Summary

中央财经大学：《大数据金融》课程教学课件（PPT讲稿）第9章 金融数据的爬虫

Data Preprocessing: An Overview Data Quality Major Tasks in Data Preprocessing Data Cleaning Data Integration Data Reduction Data Transformation and Data Discretization Summary

同济大学：《大数据分析与数据挖掘 Big Data Analysis and Mining》课程教学资源（PPT课件讲稿）关联规则 Association Rule

同济大学：《大数据分析与数据挖掘 Big Data Analysis and Mining》课程教学资源（PPT课件讲稿）K-means & EM

【人工智能】大数据智能：从数据拟合最优解到博弈对抗均衡解

Elsevier期刊全文数据库 sDOs镜像版检索系统