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मल्टीवेरिएट एडप्टिव रिग्रेशन स्प्लाइन्स (MARS)×निर्णय वृक्ष×
क्षेत्रमशीन अधिगममशीन अधिगम
परिवारMachine learningMachine learning
उद्भव वर्ष19911984
प्रवर्तकJerome H. FriedmanBreiman, Friedman, Olshen & Stone
प्रकारAdaptive piecewise-linear regressionRecursive partitioning (if-then rules)
मौलिक स्रोतFriedman, J. H. (1991). Multivariate adaptive regression splines. The Annals of Statistics, 19(1), 1–67. DOI ↗Breiman, L., Friedman, J.H., Olshen, R.A. & Stone, C.J. (1984). Classification and Regression Trees. Wadsworth. DOI ↗
उपनामmultivariate adaptive regression splines, earth algorithm, MARS regression, çok değişkenli uyarlamalı regresyon spline'larıKarar Ağacı (Decision Tree), karar ağacı, classification tree, regression tree
संबंधित45
सारांशMultivariate adaptive regression splines, introduced by Jerome Friedman in 1991, is a flexible nonparametric regression method that automatically models nonlinearities and interactions by combining piecewise-linear 'hinge' functions. It builds the model in a forward stagewise pass that adds basis functions where they help most, then prunes back the overgrown model, yielding an interpretable additive-plus-interaction form that adapts its complexity to the data.A Decision Tree is an interpretable classification and regression method, formalised by Breiman, Friedman, Olshen and Stone in their 1984 CART framework, that partitions the data with hierarchical if-then rules. Each split sends observations down one branch or another until a prediction is read off the leaf.
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