An integrated heuristic method based on piecewise regression and cluster analysis for fluctuation data (A case study on health-care: Psoriasis patients)

Trend forecasting and proper understanding of the future changes is necessary for planning in health-care area.One of the problems of analytic methods is determination of the number and location of the breakpoints, especially for fluctuation data. In this area, few researches are published when number and location of the nodes are not specified.In this paper, a clustering-based method is developed to obtain the number and the location of breakpoints. We propose an appropriate piecewise regressionmodel to analyze the fluctuation data and predict trends of them.Theefficiency of proposed integrated approach is evaluated by using a simulated and real example, and results are compared with results of Mars algorithm. Comparison shows that proposed approach has less sum of square error (SSE) criterion than Mars algorithm with equall number of nods.

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