-
Notifications
You must be signed in to change notification settings - Fork 0
Prototype Classification Method: A Quantitative Approach to Traditional Classification
The prototype classification method is a way of quantifying and digitizing things by considering them as different "aspects" obtained by transforming a standard model (prototype) through a set of feature vectors. This article will introduce the basic principles and applications of the prototype classification method, and explore its potential value in fields such as biology.
Prototype classification method; Feature vectors; Common base class; Digital specimens
Traditional classification is a science based on morphology, ecology, biogeography, and other knowledge. It classifies and generalizes biological features such as morphology and ecological habits to better understand and study biodiversity. However, traditional classification has some shortcomings, such as the subjectivity and non-quantifiability of morphological features. To address these issues, some scholars have proposed the prototype classification method, which is based on mathematical models and quantifies and digitizes things by considering them as different "aspects" obtained by transforming a standard model (prototype) through a set of feature vectors.
The basic principle of the prototype classification method is to consider a thing as different "aspects" obtained by transforming a standard model (prototype) through a set of feature vectors. This method is similar to the combination of numerical multiplication and unit. For example, using an equilateral right-angled triangle as a prototype, and using two feature vectors of the length of the two right-angled sides, different right-angled triangles can be expressed by combining this feature vector with the prototype, which is called the "aspect".
In addition, there is a common base class between different classification categories. Subcategories can be obtained by attaching specific transformations to the base class. Therefore, if two different categories have a common base class, the "aspects" of these two categories can be calculated by converting them into the base class. This method can quantify traditional classification and digitize things.
The prototype classification method has a wide range of applications in biology and other fields. For example, in insect classification, traditional classification mainly relies on insect morphology to classify them, but this method is subjective and non-quantifiable, resulting in inaccurate classification results. The prototype classification method can consider insects as different "aspects" obtained by transforming a standard model (prototype) through a set of feature vectors, which can quantify and digitize insects. By comparing and analyzing digital specimens of insects, the classification and evolutionary relationships of insects can be studied more accurately.
In addition, the prototype classification method has a wide range of applications in plant classification, animal classification, and other fields. In plant classification, the prototype classification method can quantify the morphological features of plants and study the classification and evolutionary relationships of plants. In animal classification, the prototype classification method can quantify the morphological features and ecological habits of animals, and study the classification and evolutionary relationships of animals.
The application of the prototype classification method has potential value. First, the prototype classification method can digitize things and achieve more accurate research on biodiversity. Secondly, the prototype classification method can digitize specimens and achieve storage, retrieval, and sharing of specimens. Finally, the prototype classification method can study the relationships between different categories by converting the "aspects" of different categories, providing new ideas and methods for the development of biological classification.
The prototype classification method is a way of quantifying and digitizing things by considering them as different "aspects" obtained by transforming a standard model (prototype) through a set of feature vectors. This method can quantify traditional classification and digitize things. The prototype classification method has a wide range of applications in biology and other fields, and has potential value. In the future, the prototype classification method is expected to provide new ideas and methods for the development of biological classification.