Clustan - Estimation of Missing Values and Diagnosis Using Hierarchical Classifications

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CSQ - Computational Statistics Quarterly, Vol. 2, Issue 1, 1985, page 125 - 134

by David Wishart

This paper describes an expert system for classifying cases by reference to a
hierarchical cluster analysis on a training set. It tackles the practical
problems encountered in the treatment of mixed types of data with missing
values, and allows variable weights and case weights to be specified.

Two new procedures have been implemented in the computer package Clustan. The
"Cluster" procedure obtains a hierarchical cluster analysis by 4 methods, with
a choice of 13 similarity criteria. Results are stored in a data base for use
with the "Classify" procedure, an interactive identification system which
obtains provisional class and nearest neighbour analyses on trial cases by a
fast tree traversal algorithm. Hissing values can be imputed by analogy wiih
observations on nearest neighbours or clusters.

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The following document were found together:

Reference Number : CSQ_2_1

Date Published : May 1985

Manufacturer : Physica-Verlag, Vienna, Austria

Platform : Clustan

Format : PDF (5 pages)






This exhibit has a reference ID of CH40727. Please quote this reference ID in any communication with the Centre for Computing History.

Clustan - Estimation of Missing Values and Diagnosis Using Hierarchical Classifications

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