CLASSIFICATION OF EFFECTIVE TYPE 2 DIABETIC DRUG COMBINATION USING SUPPORT VECTOR MACHINE LEARNING ALGORITHM
Abstract
Diabetes is a physiological condition characterized by high glucose in
the blood over an extended period. If it is noticed early the possibility
of survival would have been high. Most of the symptom it may
generate may be in resemblance with others disease which might be
complex for health practitioner to identify. With regard to that this
research aims to Classify Diabetic Drug Combination that would be
effective and non-effective for patient with type 2 diabetes, and one
way this can be achieved is by utilizing a modern technology approach
which is machine learning technique for the said purpose Using
Support Vector Machine Learning Algorithm.
The dataset is gotten from a General Hospital Healthcare. The dataset
is trained in order for it to be able to classify the drug combination into
effective and non-effective. With this it has been able to handle wrong
or delay in diagnosis. Our model gave an accuracy of 95% which is
deem fit with the classification of diabetes drugs
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