পদ্ধতির তুলনা করুন
নির্বাচিত পদ্ধতিগুলো পাশাপাশি পর্যালোচনা করুন; যে সারিগুলোয় পার্থক্য আছে সেগুলো চিহ্নিত করা হয়।
| ভেদাঙ্ক স্ফীতি গুণাঙ্ক (Variance Inflation Factor - VIF)× | রিজ রিগ্রেশন× | |
|---|---|---|
| ক্ষেত্র≠ | অর্থমিতি | যন্ত্র শিখন |
| পরিবার≠ | Regression model | Machine learning |
| উদ্ভবের বছর | 1970 | 1970 |
| প্রবর্তক≠ | Donald Marquardt | Hoerl, A.E. & Kennard, R.W. |
| ধরন≠ | Diagnostic statistic | L2-regularized linear regression |
| মৌলিক উৎস≠ | Marquardt, D. W. (1970). Generalized inverses, ridge regression, biased linear estimation, and nonlinear estimation. Technometrics, 12(3), 591–612. DOI ↗ | Hoerl, A.E. & Kennard, R.W. (1970). Ridge Regression: Biased Estimation for Nonorthogonal Problems. Technometrics, 12(1), 55–67. DOI ↗ |
| অপর নাম | VIF, Variance Inflation Index, Multicollinearity Inflation Factor, Varyans Enflasyon Faktörü | Ridge Regresyonu, ridge regresyonu, L2-regularized regression, Tikhonov regularization |
| সম্পর্কিত≠ | 3 | 4 |
| সারসংক্ষেপ≠ | The Variance Inflation Factor (VIF) is a scalar diagnostic statistic proposed by Donald Marquardt (1970) that quantifies how much the variance of an estimated regression coefficient increases due to linear dependence—multicollinearity—among the predictors in an ordinary least squares model. It is routinely applied in econometrics, social science, and biomedical research whenever analysts suspect that two or more independent variables move together closely enough to destabilize coefficient estimates. | Ridge Regression is an L2-regularized linear regression method, introduced by Arthur Hoerl and Robert Kennard in 1970, that reduces multicollinearity by adding a penalty on the size of the coefficients. It shrinks coefficients toward zero without setting any of them exactly to zero, producing more stable estimates when predictors are highly correlated. |
| ScholarGateডেটাসেট ↗ |
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