What is Regression | Introduction to Machine Learning for beginners | The Most Used Terms 9

Key Takeaways

regression is an instance of supervised learning which we covered in a previous video it is a reliable method of identifying which variables have an impact on a topic of interest it is used for estimating the relationships between a dependent variable often called the outcome variable and one or more independent variables often called predictors covariates or features the process of performing a regression allows you to confidently determine which factors matter most which factors can be ignored and how these factors influence each other let's see a simple example suppose attendees satisfaction with the event is our dependent variable the topics covered length of sessions food provided and the cost of a ticket are our independent variables in this case we'd want to measure the historical levels of satisfaction with the events from the past three years or so as well as any information possible in regards to the independent variables perhaps we are particularly curious about how the price of a ticket to the event has impacted levels of satisfaction to begin investigating whether or not there is a relationship between these two variables we would begin by plotting these data points on a chart with the satisfaction on the y-axis and price on the x-axis once your data is plotted you may begin to see correlations if the theoretical chart above did indeed represent the impact of ticket prices on events satisfaction then we'd be able to confidently say that the higher the ticket price the higher the levels of event satisfaction we can then trace a function representing our data as accurately as possible in this example the line would fit the data it is called linear regression the regression line represents the relationship between our independent variable the price of a ticket and our dependent variable the satisfaction in short regression is used to identify a tendency between variables and deduce an output from it there are multiple regression algorithms like linear regression polynomial regression elastic net regression and much or subscribe to not miss any of these terms clearly explained [Music] you