Identifying Disease and Diagnosis in Females Using Machine Learning

التفاصيل البيبلوغرافية
العنوان: Identifying Disease and Diagnosis in Females Using Machine Learning
المؤلفون: Sabyasachi Pramanik, Samir Kumar Bandyopadhyay
المصدر: Encyclopedia of Data Science and Machine Learning ISBN: 9781799892205
بيانات النشر: IGI Global, 2022.
سنة النشر: 2022
الوصف: Here, the researchers are trying to prepare a model for identifying whether a patient is diabetic or not. The Pima Indian Dataset has been used in this case study. There are two types of diabetes. The research consists of two stages. The first is data pre-processing, and the other is classifier construction. After pre-processing, the data classifier will be constructed which will predict whether the patient is diabetic or not. Here the researchers plan to use decision tree classifier and random tree classifier. After studying the dataset, the researchers handled the missing values in optimum ways. All the types of proposed algorithm have been described in this article.
ردمك: 978-1-79989-220-5
DOI: 10.4018/978-1-7998-9220-5.ch187
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_________::20bc64f923254921e122cdf22b85ed88
https://doi.org/10.4018/978-1-7998-9220-5.ch187
رقم الانضمام: edsair.doi...........20bc64f923254921e122cdf22b85ed88
قاعدة البيانات: OpenAIRE
الوصف
ردمك:9781799892205
DOI:10.4018/978-1-7998-9220-5.ch187