পদ্ধতির তুলনা করুন
নির্বাচিত পদ্ধতিগুলো পাশাপাশি পর্যালোচনা করুন; যে সারিগুলোয় পার্থক্য আছে সেগুলো চিহ্নিত করা হয়।
| লোএসএস / লোএসএস স্থানীয় রিগ্রেশন× | বহুপদী রিগ্রেশন× | |
|---|---|---|
| ক্ষেত্র≠ | যন্ত্র শিখন | পরিসংখ্যান |
| পরিবার≠ | Machine learning | Regression model |
| উদ্ভবের বছর≠ | 1979 | 2012 |
| প্রবর্তক≠ | William S. Cleveland | Montgomery, Peck & Vining (textbook treatment); classical least squares |
| ধরন≠ | Local nonparametric regression smoother | Linear regression in transformed predictors |
| মৌলিক উৎস≠ | Cleveland, W. S. (1979). Robust locally weighted regression and smoothing scatterplots. Journal of the American Statistical Association, 74(368), 829–836. DOI ↗ | Montgomery, D. C., Peck, E. A. & Vining, G. G. (2012). Introduction to Linear Regression Analysis. Wiley. ISBN: 978-0470542811 |
| অপর নাম≠ | LOWESS, local regression, locally weighted scatterplot smoothing, yerel regresyon | polynomial least squares, curvilinear regression, Polinom Regresyonu |
| সম্পর্কিত≠ | 3 | 4 |
| সারসংক্ষেপ≠ | LOESS (locally estimated scatterplot smoothing), introduced by William Cleveland in 1979 and extended with Susan Devlin in 1988, fits a smooth curve through data by performing a separate weighted polynomial regression in the neighbourhood of each point. Nearby observations count more than distant ones, so the method follows local structure without assuming any global functional form, making it a popular exploratory smoother for scatterplots. | Polynomial regression is a regression method that models non-linear relationships by including squared and higher-degree terms of an explanatory variable, and it is a core tool of response surface analysis. As developed in Montgomery, Peck and Vining's Introduction to Linear Regression Analysis (2012), it remains linear in its parameters even though the fitted curve bends. |
| ScholarGateডেটাসেট ↗ |
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