PERFORMANCE EVALUATION OF DATA HANDLING ALGORITHMS (DT, KNN, RF AND DNN) UNDER THE HANDLING OF TWO DATASET OF DIABETES
DOI:
https://doi.org/10.53555/7nmskx22Keywords:
Diabetes Prediction, PIDD, MDHU, KNN, DTAbstract
Diabetes is a condition that affects people of all ages these days, as everyone is aware. This paper discusses the implementation of algorithms based on two separate diabetes datasets. The algorithms were chosen based on the highest value and accuracy. In this paper analyze the four algorithms such as DT, KNN, RF and DNN. The main objective of this paper is to handle data with different and large datasets because data is the most difficult to handle. In the previous research, diabetes was predicted in different cases and their conclusions were also different. In this paper, the DNN algorithm is used and compared with other algorithms under two different datasets. In this paper, compare the DNN algorithm with the proposed algorithms such as DT, RF and KNN on large and two different datasets of diabetes. The first dataset is taken from Pima Indians Diabetes Database (PIDD) and the second dataset is collected through survey from Manjira Devi Hospital Uttarkashi (MDHU). On the basis of these two datasets, algorithms are compared.
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