Research On Application Of Plant Classification Based On Intelligence Classification Algorithms

Classification is an important research field in data mining, pattern recognition and machine learning. At present there are many methods to achieve classification, such as statistics, Support Vector Machine, Bayesian, and instance based learning, etc. Classification has wide applications, such as medical diagnosis, credit card grading system, image pattern recognition.In this paper, the Iris plant dataset is taken as an example, and it is classified by using Support Vector Machine and Bayesian algorithm. Firstly, Support Vector Machine and multiple classification is introduced. SVM algorithms based two different methods (QP and SMO) are used to classify the Iris plant. Then, Bayes and Naive Bayes Classifier(NBC) are summarized, and NBC is used to classify the Iris plant. Finally, the three methods are compared and analyzed. The experiments show that the three methods are effective to classify the Iris plant.It is an example of the application of computer technology in biology to classify the Iris plant dataset. Classification has important value in many areas of biology. Further research is to improve the algorithms, and then develop new effective classification algorithm.