পদ্ধতির তুলনা করুন
নির্বাচিত পদ্ধতিগুলো পাশাপাশি পর্যালোচনা করুন; যে সারিগুলোয় পার্থক্য আছে সেগুলো চিহ্নিত করা হয়।
| লোএসএস / লোএসএস স্থানীয় রিগ্রেশন× | রিগ্রেশন এবং স্মুথিং স্প্লাইন× | |
|---|---|---|
| ক্ষেত্র | যন্ত্র শিখন | যন্ত্র শিখন |
| পরিবার | Machine learning | Machine learning |
| উদ্ভবের বছর≠ | 1979 | 1996 |
| প্রবর্তক≠ | William S. Cleveland | Spline regression literature; P-splines by Eilers & Marx |
| ধরন≠ | Local nonparametric regression smoother | Piecewise-polynomial nonparametric regression |
| মৌলিক উৎস≠ | Cleveland, W. S. (1979). Robust locally weighted regression and smoothing scatterplots. Journal of the American Statistical Association, 74(368), 829–836. DOI ↗ | Eilers, P. H. C., & Marx, B. D. (1996). Flexible smoothing with B-splines and penalties. Statistical Science, 11(2), 89–121. DOI ↗ |
| অপর নাম≠ | LOWESS, local regression, locally weighted scatterplot smoothing, yerel regresyon | splines, cubic splines, natural splines, smoothing splines |
| 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. | Regression splines model a nonlinear relationship by fitting piecewise polynomials that join smoothly at a set of points called knots. Cubic and natural splines are the most common, and smoothing splines add a roughness penalty that automatically balances fit against smoothness. Splines are the standard flexible building block for univariate nonlinear regression and the basis of generalized additive models. |
| ScholarGateডেটাসেট ↗ |
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