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semi parametric tress shrinkage regression
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نویسنده
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khalvati fahliaynia mohamadreza ,karamikabirb hamid
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منبع
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اولين كنفرانس بين المللي دوسالانه هوش مصنوعي و علوم داده - 1403 - دوره : 1 - اولین کنفرانس بین المللی دوسالانه هوش مصنوعی و علوم داده - کد همایش: 03231-85169 - صفحه:0 -0
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چکیده
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Semi-parametric regression models combine elements of parametric and non-parametric regression approaches. lasso regression, a penalized parametric regression technique, introduces a penalty term to the regression equation to enhance model performance. regression tree models, a non-parametric approach, partition the data into subsets and build separate models for each subset. by combining these techniques, semi-parametric regression models can capture both linear and non-linear relationships in the data, providing a powerful tool for addressing complex regression problems.
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کلیدواژه
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semi-parametric regression ,lasso regression ,regression tree ,penalized regression ,non-parametric regression
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آدرس
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, iran, , iran
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پست الکترونیکی
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h_karamikabir@pgu.ac.ir
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Authors
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