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Thus, diagnosing the early stages of incidence is of great importance. In this article, a novel chaos-based stochastic model is proposed by combining the characteristics of chaotic firefly algorithm with Kernel-based Na\u00efve Bayes (KNB) algorithm for diagnosis of Parkinson\u2019s disease at an early stage. The efficiency of the model is tested on a voice measurement dataset that is collected from \u201cUC Irvine Machine Learning Repository.\u201d The dynamics of chaos optimization algorithm will enhance the firefly algorithm by introducing six types of chaotic maps which will increase the diversification and intensification capability of chaos-based firefly algorithm. The objective of chaos-based maps is to select initial values of the population of fireflies and change the value of absorption coefficient so as to increase the diversity of populations and improve the search process to achieve global optima avoiding the local optima. For selecting the most discriminant features from the search space, Na\u00efve Bayesian stochastic algorithm with kernel density estimation as learning algorithm is applied to evaluate the discriminative features from different perspectives, namely, subset size, accuracy, stability, and generalization. The experimental study of the problem established that chaos-based logistic model overshadowed other chaotic models. In addition, four widely used classifiers such as Na\u00efve Bayes classifier, k-nearest neighbor, decision tree, and radial basis function classifier are used to prove the generalization and stability of the logistic chaotic model. As a result, the model identified as the best one and could be used as a decision making tool by clinicians to diagnose Parkinson\u2019s disease patients. <\/jats:p>","DOI":"10.1177\/1550147719895210","type":"journal-article","created":{"date-parts":[[2020,1,14]],"date-time":"2020-01-14T06:34:06Z","timestamp":1578983646000},"page":"155014771989521","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":34,"title":["Hybrid chaotic firefly decision making model for Parkinson\u2019s disease diagnosis"],"prefix":"10.1177","volume":"16","author":[{"given":"Sujata","family":"Dash","sequence":"first","affiliation":[{"name":"North Orissa University, Baripada, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ajith","family":"Abraham","sequence":"additional","affiliation":[{"name":"Machine Intelligence Research (MIR) Labs, Auburn, WA, 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