Analysis of Iris Flower Event Logs using Machine Learning Techniques

Authors

  • Saravanan. M.S., Velu. C.M., S. Muthu Vijaya Pandian, Vinoth Kumar. P

Abstract

The iris flower is the type of show flower, which is normally named after the scientific name.  It is used in horticulture. Iris is widely grown as decorative plant in house and gardens. Iris grow well in most any garden soil types providing they are well-drained. First the British statistician and Biologist Ronald Fisher introduced the Iris flower dataset and defined it has multivariate feature in the year 1936 in his research article. At the same time the great scientist Edger Anderson composed the data to quantify the morphologic variation of Iris flowers from three different species, so it is called as Anderson’s Iris dataset. The iris flower has the multiple metrics with taxonomic problems. The Iris dataset collected from three species such as Iris setosa, Iris virginica and Iris versicolor by each having fifty samples. The Iris flower measured by four parameters, they are length and width of the sepals and petals in centimeters. The Iris dataset used in this research proposal as a test case for many machine learning classification techniques such as k-nearest neighbor, logistic regression and support vector machine, etc.  But this paper identifies the various species among 150 samples of the dataset to find the accuracy of classification using k-nearest neighbor and logistic regression machine learning techniques with different methods of parameter substitution.

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Published

2020-05-12

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Section

Articles