Top 10 Machine Learning Algorithms Explained

Linear Regression: For statistical techniques, linear regression is used in which the value of the dependent variable is predicted through independent variables. A relationship is formed by mapping the dependent and independent variable on a line, and that line is called the regression line, which is represented by Y a*X b where Y Dependent variable (for example, weight) X Independent Variable (e.g., height) b Intercept and a slope. Logistic Regression: In logistic regression, we have a lot of data whose classification is done by building an equation. This method is used to find the discrete dependent variable from the set of independent variables. Its goal is to find the best fit set of parameters. In this classifier, each feature is multiplied by a weight, and then all are added.