针对经典K–means算法对不均衡数据进行聚类时产生的“均匀效应”问题，提出一种基于近邻的不均衡数据聚类算法（Clustering algorithm for imbalanced data based on nearest neighbor，CABON）。CABON算法首先对数据对象进行初始聚类，通过定义的类别待定集来确定初始聚类结果中类别归属有待进一步核定的数据对象集合；并给出一种类别待定集的动态调整机制，利用近邻思想实现此集合中数据对象所属类别的重新划分，按照从集合边缘到中心的顺序将类别待定集中的数据对象依次归入其最近邻居所在的类别中，得到最终的聚类结果，以避免“均匀效应”对聚类结果的影响。将该算法与K–means、多中心的非平衡K_均值聚类方法（Imbalanced K–means clustering method with multiple centers，MC_IK）和非均匀数据的变异系数聚类算法（Coefficient of variation clustering for non-uniform data，CVCN）在人工数据集和真实数据集上分别进行实验对比，结果表明CABON算法能够有效消减K–means算法对不均衡数据聚类时所产生的“均匀效应”，聚类效果明显优于K–means、MC_IK和CVCN算法

16.1 Introduction 16.2 FURTHER DATA ANALYSIS: (MEASURED V ATTRIBUTE) 16.3 HYPOTHESIS TEST 1 16.4 HYPOTHESIS TEST 2

Oklobdzija,. C. Hamacher, Z. G. Vranesic, S. G. Zaky, J. Raymond Number Systems· Computer Arithmetic Architecture·Microprogramming 87 Programming J. M. Feldman, E. W. Czeck,. G. Lewis, J. J.Martin Assembly Language. High-Level Languages. Data Types and Data Structures

Visual Basicmicrosoft是通过 jet数据库引擎 工具来支持对数据库的数据访问能力。Visual Basic6.0提供了两种主要的与数据库引擎接口 的方法:Data控件和数据访问对象(DAO)。 Data控件是比较简单直接的方法,只给出有限 的不需编程而能访问现存数据库的功能,而 DAO模型是全面控制数据库的完整编程接口

◼ Outlier and Outlier Analysis ◼ Outlier Detection Methods ◼ Statistical Approaches ◼ Proximity-Base Approaches ◼ Clustering-Base Approaches ◼ Classification Approaches ◼ Summary

◼ Cluster Analysis: Basic Concepts ◼ Partitioning Methods ◼ Hierarchical Methods ◼ Density-Based Methods ◼ Grid-Based Methods ◼ Evaluation of Clustering ◼ Summary

◼ Classification: Basic Concepts ◼ Decision Tree Induction ◼ Bayes Classification Methods ◼ Rule-Based Classification ◼ Model Evaluation and Selection ◼ Summary

1.1 Data Handling 1. 2 Cycle Slip Detection and Repair

◼ Basic Concepts ◼ Frequent Itemset Mining Methods ◼ Which Patterns Are Interesting?—Pattern Evaluation Methods ◼ Summary

12.1 The Nature of Autocorrelation 1. Definition (1) CLRM assumption: No autocorrelation exist in dishurbances ui; E(iμi)=0 Autocorrelation means: E(μiμ)≠0 (2) Autocorrelation is usually associated with time series data, but it can also occur in cross-sectional data, which is called spatial correlation