Hola, iam Paul Hauser, Take it easy.
Hey there! Regression in simple words is a statistical technique used to predict the future based on past data. It’s a powerful tool that can help you understand how different factors affect each other and make predictions about what might happen in the future. With regression, you can identify trends, relationships, and patterns in your data that can help you make better decisions. Plus, it’s easy to use - no need for complex equations or formulas! So if you’re looking for an effective way to analyze your data and make predictions, regression is definitely worth checking out.
What Is Regression In Simple Words? [Solved]
In other words, a regression is a way to figure out if changes in one thing (the dependent variable) are related to changes in another (the independent variables). Basically, it’s like asking: “Does this affect that?” You can use it to see how different factors influence each other. Pretty cool, huh?
Linear Regression: A type of regression analysis that models the relationship between a dependent variable and one or more independent variables using a linear equation.
Logistic Regression: A type of regression analysis used to predict the probability of an outcome based on one or more independent variables.
Polynomial Regression: A type of regression analysis that models the relationship between a dependent variable and one or more independent variables using polynomial equations.
Stepwise Regression: A type of regression analysis that uses an iterative process to identify which independent variables are most important in predicting the dependent variable, and then builds a model with only those variables included in it.
Ridge Regression: A type of regression analysis that adds a penalty term to the cost function to reduce overfitting and improve generalization performance on unseen data points.
Lasso Regression: A type of regression analysis that adds an additional penalty term to the cost function, which shrinks some coefficients towards zero, thus reducing their impact on the model’s predictions and improving generalization performance on unseen data points
Regression is a statistical tool used to identify relationships between variables. In layman’s terms, it’s a way of predicting what might happen in the future based on what has happened in the past. It can help you figure out how different factors affect each other, like how changes in temperature might affect sales of ice cream. So if you want to know what could happen next, regression can give you an idea!
