Mon premier blog

Finding Groups in Data: An Introduction to Cluster Analysis Leonard Kaufman, Peter J. Rousseeuw
Publisher: Wiley-Interscience

The information obtained from the organizational survey enabled us to characterize PHC organizations. Cluster analysis is a collection of statistical methods, which identifies groups of samples that behave similarly or show similar characteristics. The organizational data were analyzed .. Rousseeuw, Finding Groups in Data: An Introduction to Cluster Analysis, John Wiley & Sons, Hoboken, NJ, USA, 2005. Hierarchical Cluster Analysis Some Basics and Algorithms 1. Introduction 1.1 What is cluster analysis? Jolliffe IT: Principal Component Analysis. Hoboken, NJ: John Wiley & Sons, Inc; 1990:1986. Data mining uses sophisticated mathematical algorithms that segment the Clustering: Finding groups of objects such that the objects in a group will be similar (or related) to one another and different from (or unrelated to) the objects in other groups. Our goal was to establish an organizational classification which would group PHC organizations based on their common characteristics. Introduction of Data mining: Data mining is a training devices that automatically search large stores of data to find patterns and trends that go beyond simple analysis. Cluster analysis is called Q-analysis (finding distinct ethnic groups using data about believes and feelings1), numerical taxonomy (biology), classification analysis (sociology, business, psychology), typology2 and so on. Kaufman L, Rousseeuw PJ: Finding Groups in Data: An Introduction to Cluster Analysis.