Comparison of machine learning techniques in the diagnosis of erythematous squamous disease

Abstract

Diagnosing a medical condition and its root cause is an involved procedure that calls for much investigation and knsowledge. Before making any health-related choices, it's crucial to have accurate information. Making a doctor's appointment is the first step in getting a diagnosis if you suspect you're unwell. The primary goal of this study is to develop a system for illness classification using machine learning techniques. The first step is to gather and prepare the data for analysis. Uncertainty in the dataset caused by noise, outliers, or missing values will be removed during pre-processing. Separate sets of Training data and Test data will be created from the preprocessed dataset. Machine learning algorithms will be used to train the model, and the resulting model will be put to the test on a separate dataset. The effectiveness of the algorithms being used in production will then be evaluated.