Analysis of Performance of Machine Learning Algorithms in Detection of Flowers

Abstract

The detection of various types of flowers, leaves, based on their characteristics, is very useful in many fields of agriculture and medical research. Machine learning algorithms are applied in this article to the identification of flowers on the basis of their characteristics. Machine learning algorithms K-nearest neighbor, Random Forest and Decision Tree are applied in a data set of flowers and their precision is calculated. Algorithms are implemented on a data collection in the Python programming language. It is found that the performance of KNN machine learning algorithm is best in detection of flowers.