Prototypal classification

There are also differences in categorical classification methods. Prototypic classification is a method that suggests the indicators for inclusion and exclusion from a category are fallible rather than perfect. In a psychiatric classification system, the patient s assignment to a category is based on the similarity of that patient to the most typical patient for that disor-... 

Implications of the prototypic classification method are that categories within the system will possess fuzzy boundaries. Individuals within a category will be somewhat heterogeneous and may not share any common features. In our depression example, a prototypic classification scheme may yield a diagnosis of depression in one patient who shows agitation, anhedonia, and suicidal ideation and the same diagnosis in another patient who shows sadness, fatigue, worthlessness, and decreased appetite. 

The project Human Error in the Process Industry within the Ergonomics Section of the Technology Work Department at the Graduate School of Industrial Engineering and Management Science was started in 1985. In order to get acquainted with the world of chemical process control two exploratory investigations were carried out in the first two years at Dutch chemical companies. This led to the development of a prototype classification model of system failure (see Chapter 5 for the most recent version). 

J.C. Bezdek and P.F. Casteiaz, Prototype Classification and Feature Selection with Fuzzy Sets, IEEE Transactions on Systems, Man, and Cybernetics, SMC-7 (1977). 87-92. 

The approach to developing metrics for process safety is analogous to those that might be used to assess Occupational Exposure risk. One can cite as well several indices that have been developed as metrics for estimating and ranking the safety of a given process or chemical reaction, such as the DOW fire and explosion index,the Stoessel index ° for hazard assessment and classification of chemical reactions, the Inherent Safety Index, the Prototype Index for Inherent Safety, amongst others. ... 

The definitions in the first section of this chapter can be useful in many ways for design, especially in the stages of search, physical prototype and manufacture. For example, the classifications of Figure 15.4-1 can help to establish the order in which different decisions related to the product must be made. For example, the procedure for a product of type 5, can start by identifying the components that contribute to the properties that are not complementary with the environment. In a second stage, we identify the most appropriate components for the complementary properties with the environment. 

Points with a constant Euclidean distance from a reference point (like the center) are located on a hypersphere (in two dimensions on a circle) points with a constant Mahalanobis distance to the center are located on a hyperellipsoid (in two dimensions on an ellipse) that envelops the cluster of object points (Figure 2.11). That means the Mahalanobis distance depends on the direction. Mahalanobis distances are used in classification methods, by measuring the distances of an unknown object to prototypes (centers, centroids) of object classes (Chapter 5). Problematic with the Mahalanobis distance is the need of the inverse of the covariance matrix which cannot be calculated with highly correlating variables. A similar approach without this drawback is the classification method SIMCA based on PC A (Section 5.3.1, Brereton 2006 Eriksson et al. 2006). 

In order to find our way among the many reactions and catalysts studied, we shall have to classify them into certain prototypes, bearing in mind that such a classification is a limitation in itself. 

An extension of this search capability to databases of bibliographic databases has been undertaken by D. Humbert. A prototype search engine has been developed. A difficulty in this search is in the classification of types of processes used by different databases. This has lead to a preliminary effort to introduce a standardized set of classifications for processes among a number of databases. 

---