Case study on Support Vector Machine| Machine Learning| SNS Institutions

A case study on a one-dimensional linear approach of Support Vector Machine (SVM) focuses on classifying data points along a single feature axis. The model identifies an optimal threshold (hyperplane in 1D) that separates the two classes with the maximum margin. Support vectors are the nearest data points to this boundary, which directly influence its position. This simple scenario helps in clearly understanding the core concept of margin maximization and decision boundaries in SVM. #snsinstitutions s #snsdesignthinkers #designthinking