Best Model Choice for a non-linear Regression (Communities - Education)
Item ID 3868471 in Category: Communities - Education
Best Model Choice for a non-linear Regression | |
There are various model options for nonlinear regression problems, with selection determined on data attributes and modelling aims. Polynomial regression extends linear regression by include polynomial terms that can capture non-linear connections. Generalised Additive Models (GAMs) provide flexibility by include smooth functions of predictor variables. Kernel regression uses weighted averages to estimate nonlinear connections. Decision trees, particularly ensemble approaches such as Random Forest or Gradient Boosting, are good at capturing complicated nonlinear patterns. Support Vector Machines (SVMs) with non-linear kernels may also successfully handle nonlinearities. Finally, the optimum option is determined by the complexity of the data, the required interpretability, and the availability of computer resources. SAS Online Training Institute, Power BI, Python Pune, India (saspowerbisasonlinetraininginstitute.in) | |
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| Target Prov.: All Provinces Target City : Pune Last Update : May 07, 2024 5:07 AM Number of Views: 61 | Item Owner : durga Gupta Contact Email: Contact Phone: +917755910537 |
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2024-12-22 (0.387 sec)