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As we have shown in Specific Case #1 where we have used a multi-stage decision-making process approach, it allows the integration of the data provided by the bottom-up approach of digitization, by the top-down approach of the foresight process, and by the heuristics approach. In particular, we take advantage of the fact that these processes explore relatively independent factors that filter, relate, or represent all sorts of data in the same way. Moreover, we achieve this with the ability to repeat the same process over and over (with different initial conditions), given that the data contain enough repetition and coverage of time. A good example can be represented by a database of books that get new contributors at any time, the creation of a database of medical patents that will be of greater interest to them if most of the records contain a patent number, or a database of DVDs that will lose its value if the collection diverges from the previous version. Furthermore, it is important to note that the three approaches are not mutually exclusive; that is, the overlapping of the databases used by the three classifiers creates a multiplicity of possibilities. In this way, the information on all of them is used together in order to extract the most relevant features of the (future) data.
This capacity for redundancy creates the aforementioned multiplicity of possibilities that provides the greatest benefit in the case of self-organized "intelligence" systems, where the steady flow of data is essential for their success. It is also true for the classification algorithms used in this article. Specifically, we know that the use of the k-NN algorithm leads to a low amount of errors (P.15 in Specific Case #1), the use of the RIPPER algorithm leads to a medium amount of errors (P.16 in Specific Case #1) and Bayeslogic leads to a high amount of errors (P.17 in Specific Case #1). We will be sure to explain the way why inferences depend on the initial conditions of the algorithm, but this will be the best explanation that we will be able to offer for our readers. d2c66b5586