Open AccessResearch on Classification Algorithm for Blackberry Lily Data
Author(s) -
Wenjun Yu,
Yu Huang
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1607/1/012099
Subject(s) - computer science , naive bayes classifier , rhizome , algorithm , artificial intelligence , botany , biology , support vector machine
Blackberry Lily is the dried rhizome of the Iris plant, which has the functions of clearing heat and detoxifying, eliminating phlegm and pharyngeal. The actual structure of its various categories is very different, and this difference is widely used by botanists to build the interspecific relationship of various varieties of Blackberry Lily. Therefore, the classification of Blackberry Lily is of great significance to the research of its evolution. In this paper, we propose several algorithms based on Naive Bayes to classify Blackberry Lily data, and some algorithms are improved.