Machine Learning in Python

Astha Baranwal, Bhagyashree R. Bagwe, V. M.
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引用次数: 4

Abstract

Diabetes is a disease of the modern world. The modern lifestyle has led to unhealthy eating habits causing type 2 diabetes. Machine learning has gained a lot of popularity in the recent days. It has applications in various fields and has proven to be increasingly effective in the medical field. The purpose of this chapter is to predict the diabetes outcome of a person based on other factors or attributes. Various machine learning algorithms like logistic regression (LR), tuned and not tuned random forest (RF), and multilayer perceptron (MLP) have been used as classifiers for diabetes prediction. This chapter also presents a comparative study of these algorithms based on various performance metrics like accuracy, sensitivity, specificity, and F1 score.
Python中的机器学习
糖尿病是现代世界的一种疾病。现代生活方式导致了不健康的饮食习惯,导致了2型糖尿病。最近,机器学习越来越受欢迎。它在各个领域都有应用,并已被证明在医学领域越来越有效。本章的目的是根据其他因素或属性来预测一个人的糖尿病结局。各种机器学习算法,如逻辑回归(LR),调谐和非调谐随机森林(RF)和多层感知器(MLP)已被用作糖尿病预测的分类器。本章还基于准确性、灵敏度、特异性和F1分数等各种性能指标对这些算法进行了比较研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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