Abstract: We show that nonlinear regression produces accurate state characterizations of in-house modeled two-qubit processors with well known gates. This regression-based tomography scheme ...

Have you ever found yourself staring at a spreadsheet, trying to make sense of all those numbers? Many face the challenge of transforming raw data into actionable insights, especially when it comes to ...

Linear regression is a type of data analysis that considers the linear relationship between a dependent variable and one or more independent variables. It is typically used to visually show the ...

Expansive soils, known for their significant volume change with variations in moisture content, are widely distributed around the globe. Due to their swelling properties, expansive soils pose ...

When you perform regression analysis in Microsoft Excel, you are engaging in a statistical process that helps you understand the relationship between variables. This technique is particularly useful ...

Ceres.js is a javascript port of the Ceres solver. Ceres Solver is an open source C++ library for modeling and solving large, complicated optimization problems. It can be used to solve Non-linear ...

Non-linear regression modeling is common in epidemiology for prediction purposes or estimating relationships between predictor and response variables. Restricted cubic spline (RCS) regression is one ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Article Views are the COUNTER-compliant sum of full text article downloads since ...

Linear / non-linear regression problem and their comparison and Convolutional Neural Network, Feed Forward Neural Network and their accuracy measurement.

Regression analysis is a statistical technique used to estimate the relationship between two or more variables. In Excel, you can perform this analysis using the built-in Data Analysis ToolPak. This ...

Linear regression is a statistical technique that helps us to understand the relationship between two variables by modeling a linear equation to observed data. There are multiple ways to conduct ...