Hi,
I prepared two bias files (kernel Density and Minimum Convex Polygon) and ran the MAXENT model twice. But the the prominent factor was different in both models.
Model with Kernel Density bias file-Type of road was the prominent factor-54.1Percent contribution, AUC 0.846)
Model with MCP bias file- BIO!2 was the prominent factor- 52.3Percent contribution)
Jackknife result also the same.
Even though I tried several times the results was the same.
Why the result is changing with the type of bias file. Which model Should I consider as final?
SU
According to “no-free lunch” theorem, it is a plain and well-known fact that no single model proved best for all kind of data set. The properties of data such as normality, size, linearity etc. affect the performance accuracy of any model. In addition, several studies have already shown that even for the same type of data set, the performance results may vary for different models. Hence, employing multiple models and combining them has been found to be effective for a variety of problems. Ensemble technique has been used with a promising success in several fields including hydro-environmental sciences, data mining and statistics as an approach to improve the prediction skill.
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