Intelligent Classifier of Patterns for celestial bodies using a Twodimensional approach

Human curiosity towards astronomy in recent decades has allowed
the development of great technological advances, which
has helped to deepen the knowledge of celestial bodies. Unfortunately,
there are still certain inconsistencies in the terminology
and classification, therefore this paper proposes the possibility of
an intelligent classification based on the features of celestial bodies
instead of calculating their electromagnetic fields. Physical
criteria are proposed obtained from the data bank of the Digital
Sky Survey which was modified in the Kaggle data repository
for discrimination between different body classes. The classification
obtained has some advantages, especially in the reduction of
time and lower computational cost on KNN (K Neighbors Classifier),
SVM, Naive Bayes Classifier, Decision Tree Classifier and
Random Forest Classifier.