ifcs

President: Carlo Lauro

Contents

From the president
Professor Chikio Hayashi
IFCS Activity Update
IFCS-2004 Update
IFCS-2002 Conference
News from the CSNA
News from SKAD
News from the SFC
News from the IPRCS
News from the GfKl
Journal of Classification
Conferences, publications

The International Federation of Classification Societies, founded in 1985, is composed of:

Associaçáo Portuguesa de Classificaçào e Análise de Dados, British Classification Society, Central American and Carribean Society of Classification and Data Analysis, Classification Society of North America, Gesellschaft für Klassifikation, Irish Pattern Recognition and Classification Society, Japanese Classification Society, Korean Classification Society, Société Francophone de Classification, Società Italiana di Statistica, Vereniging voor Ordinatie en Classificatie and Section of Classification and Data Analysis of the Polish Statistical Society.
The IFCS is a non-profit, non-political scientific organization, the aims of which are to further classification research.  Among other activities, the IFCS organises a biennial conference, and supports the Journal of Classification.
International Federation of
Classification Societies
Newsletter

Number 24                  December 2002

Editor: Krzysztof Jajuga

I would like to give the greatest thanks to Paul de Boeck for his outstanding performance while serving as Publication Officer, as well for the valuable help he gave me during the period of transferring the duties.

Krzysztof  Jajuga

From the President

Two relevant events for IFCS happened during my first year as IFCS President:
-	the bi-annual scientific meeting in Krakow;
-	the death of one of the most important IFCS Presidents we have ever had: Prof. Chikio Hayashi.
The meeting in Krakow was a great success from both the organizational and the scientific viewpoint. The crowded and qualified participation of about 200 delegates coming not only from all the societies of the Federation but also from national and international scientific societies, has allowed us to realize a comprehensive state-of-art of the important scientific achievements and developments realized in the last years in the field of classification and data analysis, computational statistics theory and all related applications.
The excellent social program and the great atmosphere created by our guests in the wonderful scenario of Krakow have certainly encouraged scientific exchanges and increased the feeling of membership to the IFCS. They also have consolidated the friendship and the brotherhood of people in this difficult period of our history where the worries related to the present political situation need strong hopes and beliefs.
In the name of all the participants at the IFCS-2002 I wish to express my warmest thanks and congratulations to the Scientific Committee and to the local Organizing Committee, in particular to Krzysztof Jajuga and Andrzej Sokołowski for their 

efforts and quality of work done for the benefit of IFCS.
The IFCS Council, during a very interesting meeting hold in Krakow, has established to direct all the activities of the Federation along three important policies:
-	to widen the scientific sphere of IFCS influence in the international community;
-	to enlarge the participation of individual members to the activities promoted and run by the Federation;
-	to realize a real and effective publication policy of the Federation.
Many committees have already been established and are already working in order to realize these aims. Some important results are already visible, many others are on the way.
Among the undertaken actions, the following are worth pointing out:
-	in the Krakow meeting, the SDA (Symbolic Data Analysis) transversal group was created;
-	the program of the next IFCS session (Chicago, USA, 2004) is going to show a high scientific profile thanks to the work of David Banks and Buck Mc Morris as well as of all the colleagues that are participating in the organization;
-	direct participation of IFCS in the scientific committees of COMPSTAT 2004 (organized by Jaromir Antoch in Prague), CARME 2003 (organized by Michael Greenacre in Barcelona), IMPS 2003( organized by Jacqueline Meulman in Cagliari, Italy). These conferences will also include sessions offering applications and developments of the classification methodologies in different contexts. IFCS is starting to widen its sphere of influence by getting in touch and starting co-operation with other societies and groups of research;
-	organization (by Helena Bacelar in Lisbon – July 2003) of a summer school and a workshop on the themes related to Classification and Data Mining as an IASC-IFCS joint event;
-	at last, I want to highlight the big interest shown by the Chinese statistical researchers to be active as a part of the Federation.
The summer school in Portugal is jointly organized with IASC (International Association for Statistical Computing) section of ISI. A broader cooperation agreement has been recently established with IASC by means of its Chairman, Prof. J.C. Lee. IASC will participate with its delegates to the Chicago session of IFCS, while IFCS participates in the COMPSTAT 2004 scientific committee. A similar agreement has been established with the President of the Psychometric Society (J. Meulman) for starting fruitful exchanges in occasion of IMPS'03 and IFCS '04.
Important contacts have also been started with the ISI: H. Bock is the organizer of a session concerning classification and clustering at the next ISI scientific meeting (Berlin, August 2003).
In this year, IFCS was struck by the terrible news of Prof. Hayashi's death. It was a very great sorrow to the International Federation of Classification Societies to learn of this death. He was one of the pioneers in the field of Classification, and one of the most outstanding leaders of IFCS. Besides his scientific brilliance and fresh ideas (among others, data theory really represents a breakthrough) I will always remember his distinction as well as his respect for any colleagues (with a special care and love for the youngest ones) and his interest in any novelty. His Presidency in IFCS was distinguished by a great capacity as an administrator and as a solver of many crucial matters but also as a great visionnaire. I feel honored to be among of its successors and now to carry the burden, as IFCS President, of aiming at accomplishing some of his dreams for the Federation.

Carlo Lauro
IFCS President

Prof. Carlo Lauro
Dipartimento di Matematica e Statistica
Universita' degli Studi di Napoli "Federico II"
Via Cintia - Complesso Monte Sant'Angelo
I-80126 Napoli
tel.: +39 081 675189 fax: +39 081 675113
E-mail: carlo.lauro@unina.it

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PROFESSOR CHIKIO HAYASHI

Professor Chikio Hayashi and Multidimensional Data Analysis – 
Quantification  Methods and Data Analysis, from Classification to Data Science

Professor Chikio Hayashi is no longer with us.  We have lost a great man. To me, his death marks the loss of a valued mentor who acted as a guide not only in the field of statistics but also through the confusion that exists today in the fields of social research and data analysis.
In this tribute to Professor Hayashi, I have drawn upon thirty years of memories.  I treasure the simple ones most – sharing a room on a tour of the Loire River in France, going on an excursion with the professor and his wife in the intense heat of Morocco, trying to decide how much to pay for a carpet, walking together in midday at Rome, and accompanying the professor on countless occasions to different restaurants overseas. I can still see him, wearing his trademark beret, encouraging me to do my best because he is relying on me. At such times I am overcome with emotion. 
I cannot describe the full extent of Professor Hayashi's achievements.  If I started, there would be no end.   Instead I shall write about some of the memories I have of our long relationship.  I hope this tribute to him will show the Professor Hayashi that I knew and some things that are not commonly known about him. 

The Teachings of a Highly Inquisitive Educator

Professor Hayashi had extraordinary knowledge in many areas. His diverse interests included music, sports, books, calligraphy and the tea ceremony. When a new topic came up, he would often telephone me at the laboratory and say: "Look, there's apparently some new research going on in such and such, do you know about it?" or "If you've got any information or materials on such and such, let me have them." Once he had read the latest information, he quickly formed an opinion, and thus followed the modern work in fractals, genetic algorithms, neural networks, rough set theory, complex systems, support vector machines, data mining, and knowledge discovery. 
Professor Hayashi knew how to manage people efficiently.  He had an extensive personal network through which he constantly gathered the latest information. One thing he taught me was that this kind of attention to detail is an essential for researchers, particularly in statistics and data analysis. Whenever I approach a problem from the professor's perspective I see it in a different light, and I am grateful for this gift of understanding.  Looking back, I believe this approach was part of the professor's unique teaching method. 

Multidimensional Data Analysis and Multivariable Analysis – These Are Two Different Things

Professor Hayashi strongly believed that reality is understood through the careful use of words. This is obviously true for a research paper but the professor went further in his approach to technical terms. For example, he would call "statistics" by that name alone and disliked the phrase "statistical science." Similarly, he insisted on the term "multidimensional data analysis" as opposed to "multivariate analysis". People with less insight often said that either term was acceptable but the professor would not allow this. 
I once asked Professor Hayashi to read through an article I wrote on multidimensional data analysis. When he returned it I found that he had crossed out the phrase “multivariate analysis” everywhere and had even made a marginal note that "use of that term degrades your paper." Yet he had also written "you're quite right," and "this is good; it's consistent with my view" next to parts he liked. Nonetheless, he was never a nit-picker. He did not concern himself much over trivia such as misspellings, and he was happy as long as the essence of the analysis and the main points were conveyed.  This was also true of his teaching style. 
In any event, multivariate analysis for him was just an unnecessarily complex arithmetical operation based on Gaussian distributions that had too many restrictions for practical use and could only be applied in research papers. He lamented that there were too many cases where "you can't see the wood for the trees."

Quantification for Exploring Phenomena and Acquiring Information

Most researchers refer to Hayashi's quantification theory but in his books the professor simply called it "quantification." And although Professor Hiroshi Akuto’s names for the quantification methods (Types I-VI) are now common, Professor Hayashi himself called them by different names, reflecting their respective ways of thinking. But Professor Hayashi frequently commented that Professor Akuto's names helped spread the quantification methods. I can only admire this kind of consideration for other people's feelings. 
The origin of the quantification method derives from the idea that "numbers (numerical values) do not exist ahead of time but are allocated as appropriate 

in accordance with our objectives." Thus we should make a clear distinction between (possibly non-numeric) raw measurements and numeric values used for analysis. While there are common ways to give numerical value to qualitative data, a different approach states that since many things in the world are nonlinear, we should approximate these in an easily manageable linear form, devise creative experiments, and solve problems through data collection and analysis methods appropriate to the phenomena. This approach requires detailed modeling, and is the antithesis of the approach (used by many statisticians) that fits data to a simple conventional model. I believe that the essence of Professor Hayashi’s thinking on this is still not properly understood within mainstream statistics, and his efforts to explain this led him to emphasize "data science" in his later years.

First Acquaintance with Professor Benzécri and Correspondence Analysis

In the early 1960s, Professor Benzécri developed the AFC method (analyse des factorielle correspondances, or correspondence analysis). His work formed the basis for data analysis (analyse des données) in France. Professor Benzécri strongly criticized the existing mathematical statistical approach and his unique lectures at University of Paris VI became widely known. 
Some people pointed out that AFC appeared to be the same as quantification method Type III. As expected, Professor Hayashi conducted a detective-like investigation, even going so far as to question the existence of Professor Benzécri and to wonder whether it wasn't a research organization like Bourbaki. His doubts were resolved, however, in 1979 when Professor Hayashi and Professor Benzécri met for the first time. Professor Benzécri subsequently wrote: "I was surprised that, of all places, it was the Far East where there was a researcher who had come up with the same ideas as me, and quite clearly earlier than I had." In this way it became known throughout Europe that quantitative method Type III was the same as correspondence analysis. However, Professor Hayashi insisted that although there were similarities in equations and formulation, the basic ideas and philosophies behind were different.  Professor Hayashi's foresight in the analysis of qualitative information stood out and this approach became widely known overseas. 

Research Exchange between Japan and France – International Exchange in Data Analysis

Data analysis, particularly EDA (Exploratory Data Analysis), is an approach advocated by Dr. J. Tukey in the early 1960s, at about the same time as the appearance of AFC.  Professor Hayashi noted this early on but pointed out that although there were common aspects with his concept of data analysis, Tukey’s EDA assumed only limited data. The analysis envisaged by the Professor Hayashi was linked more closely to practi