Performance Evaluation of Supervised Learning for Iris Flower Species

Performance Evaluation of Supervised Learning for Iris Flower Species
Author(s):
Shivam Vatshayan
Keywords:

Abstract
Machine Learning is a field of computer science pro-vides the ability to learn without programming and the program explicitly. Supervised Machine Learning (SML) is the search for algorithms that reason from externally supplied instances to produce general hy-potheses, which then make predictions about future in-stances. Classification and Regression is a supervised learning in which the response is categorical that is its values are in finite Discrete and continuous set. To sim-ply the problem of classification, scikit learn tools has been used. This paper focuses on IRIS flower classifica-tion using Machine Learning with scikit tools. In this paper we will train the machine learning model with the given Iris Dataset and Analysis the performance and accuracy of Iris with Supervised Learning Algo-rithms.
Article Details
Unique Paper ID: 147862 Publication Volume & Issue: Volume 5, Issue 11 Page(s): 178 - 183
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