High-dimensional asymptotics of prediction: Ridge regression and classification

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Robust Ridge Regression for High-Dimensional Data

Ridge regression, being based on the minimization of a quadratic loss function, is sensitive to outliers. Current proposals for robust ridge regression estimators are sensitive to “bad leverage observations”, cannot be employed when the number of predictors p is larger than the number of observations n; and have a low robustness when the ratio p=n is large. In this paper a ridge regression esti...

متن کامل

High-dimensional classification by sparse logistic regression

We consider high-dimensional binary classification by sparse logistic regression. We propose a model/feature selection procedure based on penalized maximum likelihood with a complexity penalty on the model size and derive the non-asymptotic bounds for the resulting misclassification excess risk. The bounds can be reduced under the additional low-noise condition. The proposed complexity penalty ...

متن کامل

Ridge regression ensemble for toxicity prediction

Traditional methods of assessing chemical toxicity of various compounds require tests on animals, which raises ethical concerns and is expensive. Current legislation may lead to a further increase of demand for laboratory animals in the next years. As a result, automatically generated predictions using Quantitative Structure–Activity Relationship (QSAR) modelling approaches appear as an attract...

متن کامل

Prediction of chronological age based on Demirjian dental age using robust ridge regression method

Introduction: Estimation of age has an important role in legal medicine, endocrine diseases and clinical dentistry. Correspondingly, evaluation of dental development stages is more valuable than tooth erosion. In this research, the modeling of calendar age has been done using new and rich statistical methods. Considerably, it can be considering as a practicable method in medical science that is...

متن کامل

Unbiased Prediction and Feature Selection in High-Dimensional Survival Regression

With widespread availability of omics profiling techniques, the analysis and interpretation of high-dimensional omics data, for example, for biomarkers, is becoming an increasingly important part of clinical medicine because such datasets constitute a promising resource for predicting survival outcomes. However, early experience has shown that biomarkers often generalize poorly. Thus, it is cru...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: The Annals of Statistics

سال: 2018

ISSN: 0090-5364

DOI: 10.1214/17-aos1549