Linear regression is the most fundamental machine learning technique to create a model that predicts a single numeric value. One of the three most common techniques to train a linear regression model ...
Dr. James McCaffrey presents a complete end-to-end demonstration of the kernel ridge regression technique to predict a single numeric value. The demo uses stochastic gradient descent, one of two ...
Gene Expression Programming (GEP) is a popular and established evolutionary algorithm for automatic generation of computer programs and mathematical models. It has found wide applications in symbolic ...
In this tutorial, we’ll build on the foundation laid in the “Arduino-Based Solar Power System Using Python & Machine Learning, Part 1” project by exploring how to intelligently select and use machine ...
Abstract: In this paper, a hardware design based on the field programmable gate array (FPGA) to implement a linear regression algorithm is presented. The arithmetic operations were optimized by ...
STreeD is a framework for optimal binary decision trees with separable optimization tasks. A separable optimization task is a task that can be optimized separately for the left and right subtree. The ...
The accounting press has heralded the growing and transformational use of data analytics in accounting—auditing in particular. A recent poll regarding top priorities for audit leaders conducted by ...
Article Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results