Logistic Regression is a widely used model in Machine Learning. It is used in binary classification, where output variable can only take binary values. Some real world examples where Logistic ...

Linear regression is a powerful and long-established statistical tool that is commonly used across applied sciences, economics and many other fields. Linear regression considers the relationship ...

Linear regression models predict the outcome of one variable based on the value of another, correlated variable. Excel 2013 can compare this data to determine the correlation which is defined by a ...

Abstract: Differential equations are used to predict a wide range of phenomena in physics, engineering, and other fields. In education, differential equations are usually introduced axiomatically, and ...

ABSTRACT: This research aims to develop reliable models using machine learning algorithms to precisely predict Total Dissolved Solids (TDS) in wells of the Permian basin, Winkler County, Texas. The ...

Abstract: In our previous work, we have applied ordinary linear regression equation to network anomaly detection. However, the performance of ordinary linear regression equation is susceptible to ...

Introduction: Depression and obesity are the main threat among women which have been considered by many research scholars in psychology studies. In their analysis for measuring and estimating obesity ...

Ridge regression is a type of linear regression that includes a regularization term to prevent overfitting by penalizing large coefficients, improving the model’s generalization to new data. Ridge ...

Non-parametric regression is a type of statistical analysis that makes no assumptions about the functional form of the relationship between variables. Non-parametric regression is a statistical method ...