Diagnosis of Denizen Cirrhosis Disorders Using Supervised Machine Learning Classifiers

被引：0

作者：

Patel, Sagar ^{[1
]}

Shah, Chintan ^{[1
]}

Patel, Premal ^{[1
]}

Rathod, Dushyantsinh ^{[2
]}

机构：

[1] Silver Oak Univ, Aditya Silver Oak Inst Technol, Dept Comp Engn, Ahmadabad, Gujarat, India

[2] Sankalchand Patel Univ, Dept Comp Engn, Visnagar, Gujarat, India

来源：

PROCEEDINGS OF SEVENTH INTERNATIONAL CONGRESS ON INFORMATION AND COMMUNICATION TECHNOLOGY, VOL 4 | 2023年 / 465卷

关键词：

AI and ML; Denizen disease; Classification report; Confusion matrix; CLASSIFICATION;

D O I：

10.1007/978-981-19-2397-5_72

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, we are predicting Denizen disease. In this paper, I am using many ML classifier likewise logistic regression, random forest, bagging classifier, extra tree classifier, and hist-gradient boosting classifiers. These are used to identify Denizen diseases. It predicted the final outcome based on various classifiers. Based on an efficient model, we propose the approach which provides perfect trained model to predict whether a person is having at risk for Denizen disease or not. The dataset is taken from Kaggle.

引用

页码：809 / 815

页数：7

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