Published Paper Details:

Machine Learning appears as one of the key features to derive information from corporate operating datasets. Machine Learning in medical health care evolving as an enormous research field for delivering deeper understanding on medical data. Most methods of machine learning depend on several features defining the behavior of the algorithm, influencing the output, and thus the complexity of the resulting models either directly or indirectly. Many Machine Learning methods are utilized within the past to detect diseases. Prior detection of disease or low immune can help person to reinforce immune so on guard our body from harmful germs and viruses. Process is completed with the assistance of things like RBC counts, WBC, HB, MCV, MCH, MCHC, Neutrophils and platelet count. Observing and identifying of immune isn't an easy task to do manually because it takes a lot of time and effort. So it's easier to predict immune with an automatic processing and Machine Learning System. Different types of knowledge processing and Machine Learning algorithms are available to make best algorithm like rectilinear regression, Logistic regression and KNN algorithm. Various machine learning algorithm are often used to predict, so that the immune can often predicted easily and clearly because accuracy is vital in machine learning algorithm. This paper presents a study of various methods of predicting human immune.