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Found 4 papers, 0 papers with code
Estimation of the parameters of an infectious disease model using neural networks
In this paper, we propose a realistic mathematical model taking into account the mutual interference among the interacting populations.
Novel Approaches for Predicting Risk Factors of Atherosclerosis
The decision rules extracted by our methodology are able to predict the risk factors with an accuracy of $99. 73%$ which is higher than the accuracies obtained by application of the state-of-the-art machine learning techniques presently being employed in the identification of atherosclerosis risk studies.
Performance comparison of State-of-the-art Missing Value Imputation Algorithms on Some Bench mark Datasets
Decision making from data involves identifying a set of attributes that contribute to effective decision making through computational intelligence.
Alternating Decision trees for early diagnosis of dengue fever
We have developed and trained an alternating decision tree with boosting and compared its performance with C4. 5 algorithm for dengue disease diagnosis.
