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By Gérard Govaert

The 1st a part of this publication is dedicated to tools looking appropriate dimensions of information. The variables therefore received offer a man-made description which frequently ends up in a graphical illustration of the knowledge. After a common presentation of the discriminating research, the second one half is dedicated to clustering equipment which represent one other procedure, frequently complementary to the equipment defined within the first half, to synthesize and to investigate the information. The publication concludes by way of analyzing the hyperlinks present among information mining and knowledge research.

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Fs (i)2 + Ft (i)2 ] . 3. e. (projected inertia)/(total inertia) which, for a point, can be interpreted as a square cosine. Thus, for the row i and rank s axis: Inertia of the point i projected on the axis s fi. [Fs (i)]2 = = cos2 θis Global inertia of the point i fi. 5). Qualities of representation of the same point on several axes can be summed. 5): (cosθiP )2 = (cos θis )2 + (cos θit )2 . e. the difference between its profile and the average profile) can only be completely described by taking into account at least one other dimension.

Inertia of the category j: 1 Q (1 − nj n ) In the calculation of its inertia, the eccentricity of a rare category is attenuated by its low weight but remains influential. 8 times higher than that of a category possessed by 50% of the individuals. It is therefore advisable to avoid the rare categories as far as possible, even if the total number of individuals is very high. In this way, when an a priori gathering of categories is not available, software SPAD (système pour l’analyse des données) [SPA 01] proposes a random ventilation (in the other categories) of the categories whose frequency is lower than a threshold fixed by the user (the default value is 2%).

In this case, carrying out CA on the initial contingency table or on the table in which the two rows i and were summed leads to the same result. This property, seemingly technical, has a concrete impact. To build the SEC × candidates table quoted at the beginning of this chapter, it is therefore necessary to first choose the level of detail of the variable SEC. We can suspect, for example, that distinguishing the various levels of qualification of the professional workmen brings nothing in the sense that the classes thus defined have the same profile of votes.

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