Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...
Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with pseudo-inverse training implemented using JavaScript. Compared to other training techniques, such as ...
1 Department of Information Technology and Computer Science, School of Computing and Mathematics, The Cooperative University of Kenya, Nairobi, Kenya. 2 Department of Computing and Informatics, School ...
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 ...
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 ...
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 ...
Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the linear support vector regression (linear SVR) technique, where the goal is to predict a single numeric ...
ABSTRACT: Burundi faces major agricultural constraints, including land fragmentation, soil erosion, limited access to inputs, inadequate infrastructure and demographic pressures that exacerbate food ...
Prediction of profits for a food truck using Linear Regression algorithm in Matlab programming language. Also using Gradient Descent to optimize parameters and Data visualization. This week we’re ...
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