A new medical decision making system: Least square support vector machine (LSSVM) with Fuzzy Weighting Pre-processing

The use of machine learning tools in medical diagnosis is increasing gradually. This is mainly because the effectiveness of classification and recognition systems has improved in a great deal to help medical experts in diagnosing diseases. This study aims at diagnosing Liver Disorder with a new hybrid machine learning method. By hybridizing LSSVM with Fuzzy Weighting Pre-processing, a method was obtained to solve this diagnosis problem via classifying Liver Disorder. Fuzzy Weighting Pre-processing stage was developed firstly in our study. This Liver Disorder dataset is a very commonly used dataset in literature relating the use of classification systems for Liver Disorder Diagnosis and it was used in this study to compare the classification performance of our proposed method with regard other studies. We obtained a classification accuracy of 94.29%, which is the highest one reached so far. This result is for Liver Disorder but it states that this method can be used confidently for other medical diseases diagnosis problems, too.