The distance between a point on the graph and the regression line is known as the prediction error. The equation creates a line, hence the term linear, that best fits the X and Y variables provided. The result should be a linear regression equation that can predict future students’ results based on the hours they study. The data scientist trains the algorithm by refining its parameters until it delivers results that correspond to the known dataset. The student inputs a portion of a set of known results as training data. ![]() It’s used for finding the relationship between the two variables and predicting future results based on past relationships.įor example, a data science student could build a model to predict the grades earned in a class based on the hours that individual students study. Linear regression is a supervised learning algorithm that compares input (X) and output (Y) variables based on labeled data. Statistics Concepts for Data Scientists.Home / Learning / Machine Learning Algorithms / Linear Regression What is Data Visualization? expand_more.Machine Learning Algorithms expand_more.Statistics Concepts for Data Scientists expand_more.What Can You Do With a Computer Science Degree?.How to Become a Business Analyst With No Experience.Best Master’s in Information Systems expand_more.Online Master’s in Cybersecurity expand_more.Online Master’s in Computer Engineering.Best Master’s in Business Analytics expand_more. ![]() Master’s in Data Science Programs in Washington, D.C.Master’s in Data Science Programs in Texas.Master’s in Data Science Programs in Ohio.Master’s in Data Science Programs in New York.Master’s in Data Science Programs in Colorado.Master’s in Data Science Programs in California.Online Data Science Master’s Degrees in 2023. ![]() Best Master’s in Data Science expand_more.
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