![]() As we show, statistical learning theory provides interesting insights on the question whether simplicity is a road to the truth, and whether simpler models should be preferred to more complex ones in general. The main aim of statistical learning theory is to investigate properties of learning algorithms according to a statistical framework, deriving bounds on their performance (Bousquet et al., 2004). Instead, we take a more direct approach with a more modest aim, focusing on statistical learning theory, a formal framework in the field of machine learning which allows for a mathematically rigorous treatment of the principles of simplex sigillum veri and of Occam’s razor. In this paper, we don’t aim at providing a full “theory of simplicity”. In short, understanding whether, and why, simplicity is actually evidence of the truth would require a treatment of many different issues on which the philosophical debate is not settled at all. Third, one should provide a rational justification of the relevant simplicity principles, showing that they are defensible on conceptual grounds and effective in their intended purpose. Second, one needs to investigate how the defined notion of simplicity is effectively used by physicists, statisticians, economists, philosophers, and other scholars in their daily work. First, an adequate definition of simplicity is needed, distinguishing, for instance, between “simple” as “elegant” (i.e., mathematically or syntactically simple), and “simple” as “parsimonious” (with reference to the number and complexity of entities and commitments assumed on the ontological or metaphysical level). Clarifying these two intuitions, and their relationship, has however proven surprisingly difficult (Baker, 2016 Sober, 2015 Fitzpatrick, 2013).įollowing Baker ( 2016), one can point to three main critical issues. It is often connected with another principle, usually known as Occam’s razor: that, all other things being equal, simpler theories, models, and explanations should be preferred over more complex ones. This latter idea-that “simplicity is a sign of truth” ( simplex sigillum veri)-has a venerable history in both science and philosophy. Simpler models and theories are not only more manageable from a cognitive and computational point of view, but are also perceived as more likely candidates for true or credible explanations in the relevant domains. ![]() In Server Explorer, open the Student table designer by double-clicking the Student table.In many areas of science, a preference for simplicity is often defended as an important methodological principle. ![]() Enter the following commands in the PMC to create another migration: add-migration ColumnFirstName The addition of the Column attribute changes the model backing the SchoolContext, so it won't match the database. In Models\Student.cs, add a using statement for the namespace and add DataType and DisplayFormat attributes to the EnrollmentDate property, as shown in the following example: using System To see an example of how to do that, you'll add an attribute to the EnrollmentDate property in the Student class. By using data annotation attributes, you can make one code change that will fix the display format in every view that shows the data. The DataType Attributeįor student enrollment dates, all of the web pages currently display the time along with the date, although all you care about for this field is the date. ![]() Then in several of the following sections you'll create the complete School data model by adding attributes to the classes you already created and creating new classes for the remaining entity types in the model. In this section you'll see how to customize the data model by using attributes that specify formatting, validation, and database mapping rules. ![]()
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