Non-Linear Regression in R – feed forward neural networks in R Non-linear regression is a type of statistical analysis that is used to model relationships between variables that are not linear. In other words, it is used to model relationships where the change in one variable is not directly proportional to the change in another …
Non-Linear Regression in R – cubist algorithm in R Non-Linear Regression is a type of regression that can be used to model complex relationships between variables. One type of non-linear regression is called the Cubist algorithm, which is a machine learning algorithm that can be used to make predictions in complex datasets. It is a …
Non-Linear Regression in R – conditional regression trees in R Non-Linear Regression is a type of regression that can be used to model complex relationships between variables. Unlike linear regression, where the relationship between the predictor and response variables is represented by a straight line, non-linear regression models can represent more complex relationships using different …
How to do lasso regression in R Lasso regression is a type of linear regression that adds a regularization term to the equation. This helps to prevent overfitting, which occurs when a model is too complex and is able to fit the noise in the data instead of the actual underlying trend. The “lasso” part …
How to do elastic net regression in R Elastic net regression is a method of linear regression that combines the strengths of two other methods, Lasso and Ridge regression. Like Lasso regression, Elastic net adds a penalty term to the linear regression equation to shrink the coefficients of the independent variables towards zero. This helps …
Linear Regression in R – principal component regression in R Linear regression is a statistical method used to understand the relationship between a dependent variable (also known as the outcome or response variable) and one or more independent variables (also known as predictors or explanatory variables). In other words, it is used to predict the …
Linear Regression in R – partial least squares regression in R Linear Regression is a statistical method used to understand the relationship between a dependent variable and one or more independent variables. However, when the number of independent variables is large, linear regression can become difficult to interpret and may not be able to accurately …
Linear Regression in R – ordinary least squares regression in R Linear regression is a statistical method used to understand the relationship between a dependent variable and one or more independent variables. The goal of linear regression is to find the line of best fit that describes the relationship between the variables. One of the …
Regression Analysis in R – How to visualise Visualization is the process of creating graphical representations of data to make it easier to understand and analyze. In R, there are several ways to visualize data, and one of them is by using the base R functions and packages such as “ggplot2”, “lattice” and “plotly”. The …
Regression Analysis in R – How to use predict function Regression analysis is a statistical method that is used to examine the relationship between one or more independent variables and a dependent variable. In R, there are several ways to perform regression analysis, and one of them is by using the base R functions and …