When applying data-mining techniques to real-world data, we often find ourselves facing
observations that have no value recorded for some attributes. This can be caused by several …

Random forests (RF) is known as an efficient algorithm in classification, however it depends
on the integrity of datasets. Conventional methods in dealing with missing values usually …

Missing data is a common problem in real-world data sets and it is amongst the most
complex topics in computer science and many other research domains. The common ways …

This chapter introduces the anatomy and physiology of the respiratory system, and the
reasons for measuring breathing events, particularly, using wearable sensors. Respiratory …

The accurate estimation of missing data plays a vital role in ensuring a high level of data
quality. The missing values should be imputed before performing data mining, machine …

Abstract The University of California Irvine Heart disease dataset had missing data on
several attributes. The missing data can loss the important information of the attributes, but it …

Respiratory diseases such as Asthma, COVID-19, etc., require preventive and precautionary
measures. Due to the lack of medical treatment for the masses, researchers are currently …

Abstract Chronic Kidney Disease (CKD) is one of the most widespread illnesses in the
United States. Recent statistics show that twenty-six million adults in the United States have …