Abstract: Mixed linear regression (MLR) models nonlinear data as a mixture of linear components. When noise is Gaussian, the Expectation-Maximization (EM) algorithm is commonly used for maximum ...
This C library provides efficient implementations of linear regression algorithms, including support for stochastic gradient descent (SGD) and data normalization techniques. It is designed for easy ...
The modern internet is ruled by algorithms. When you boot up Instagram, for example, what you see in your feed is strategically sorted by the app's AI based on your past activity to keep you engaged ...
Background: Multiple sclerosis (MS) is a chronic neuroinflammatory disorder characterized by demyelination and immune dysregulation, and microglia play a central role in disease progression. Despite ...
The Department of the Air Force’s process for determining if airmen and Space Force guardians should receive medical waivers for shaving is about as indecipherable as the infamous flow chart about ...
Abstract: The purpose of this work is to improve the detection of fraud websites using Novel Linear Regression Algorithm and Recurrent Neural Network Algorithm. Materials and Methods: Novel Linear ...
Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the AdaBoost.R2 algorithm for regression problems (where the goal is to predict a single numeric value). The ...
Banks are important for the development of economies in any financial ecosystem through consumer and business loans. Lending, however, presents risks; thus, banks have to determine the applicant’s ...
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