Results 1 to 10 of about 2,939,863 (258)
Minimizing Stochastic Complexity with Ridge Regression [PDF]
We derive a penalty strength criterion for ridge regression using stochastic complexity, which is a refined variant of the minimum description length principle.
Antony Mizzi +2 more
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FPGA-Based Implementation of Stochastic Configuration Networks for Regression Prediction
The implementation of neural network regression prediction based on digital circuits is one of the challenging problems in the field of machine learning and cognitive recognition, and it is also an effective way to relieve the pressure of the Internet in
Yunqi Gao +4 more
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Inferring structure and parameters of stochastic reaction networks with logistic regression. [PDF]
Identifying network structure and estimating reaction parameters remain central challenges in modeling chemical reaction networks. In this work, we develop likelihood-based methods that use multinomial logistic regression to infer both stoichiometries ...
Boseung Choi +2 more
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Evaluation of Mutual Information and Feature Selection for SARS-CoV-2 Respiratory Infection
This study aims to develop a predictive model for SARS-CoV-2 using machine-learning techniques and to explore various feature selection methods to enhance the accuracy of predictions. A precise forecast of the SARS-CoV-2 respiratory infections spread can
Sekar Kidambi Raju +6 more
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Estimation of Stationary Stochastic Coefficient Regression Models [PDF]
In this paper an attempt is made to estimate a regression equation using a time series of cross-sections. It is assumed that the stochastic coefficient regression vector is distributed across individuals with the same mean and the same variance ...
Farid E. Abdel-Badie +1 more
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Granular Elastic Network Regression with Stochastic Gradient Descent
Linear regression is the use of linear functions to model the relationship between a dependent variable and one or more independent variables. Linear regression models have been widely used in various fields such as finance, industry, and medicine.
Linjie He +3 more
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A New Lifetime Model, Stochastic Orders and Kidney Infection Regression Model [PDF]
We introduce a method to generate a new class of lifetime models based on the bounded distributions such that the defined models are exclusively a special case of the new class.
Araf Khanjari Idenak +2 more
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Periodic Fluctuations in the Incidence of Gastrointestinal Cancer
PurposeNative stem cells can be periodically replaced during short and long epigenetic intervals. Cancer-prone new stem cells might bring about periodic (non-stochastic) carcinogenic events rather than stochastic events.
Mun-Gan Rhyu +5 more
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Generalized Stochastic Restricted LARS Algorithm
The Least Absolute Shrinkage and Selection Operator (LASSO) is used to tackle both the multicollinearity issue and the variable selection concurrently in the linear regression model.
Manickavasagar Kayanan +1 more
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Modeling and Calibration for Some Stochastic Differential Models
In many scientific fields, the dynamics of the system are often known, and the main challenge is to estimate the parameters that model the behavior of the system.
Abdelmalik Moujahid, Fernando Vadillo
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