A computationally fast variable importance test for random forests for high-dimensional data
نویسندگان
چکیده
منابع مشابه
A computationally fast variable importance test for random forests for high-dimensional data
Random forests are a commonly used tool for classification with high-dimensional data as well as for ranking candidate predictors based on the so-called variable importance measures. There are different importance measures for ranking predictor variables, the two most common measures are the Gini importance and the permutation importance. The latter has been found to be more reliable than the G...
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هدف اصلی از این تحقیق به دست آوردن و مقایسه حق بیمه باورمندی در مدل های شمارشی گزارش نشده برای داده های طولی می باشد. در این تحقیق حق بیمه های پبش گویی بر اساس توابع ضرر مربع خطا و نمایی محاسبه شده و با هم مقایسه می شود. تمایل به گرفتن پاداش و جایزه یکی از دلایل مهم برای گزارش ندادن تصادفات می باشد و افراد برای استفاده از تخفیف اغلب از گزارش تصادفات با هزینه پائین خودداری می کنند، در این تحقیق ...
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ژورنال
عنوان ژورنال: Advances in Data Analysis and Classification
سال: 2016
ISSN: 1862-5347,1862-5355
DOI: 10.1007/s11634-016-0270-x