Data Science Revealed: With Feature Engineering, Data Visualization, Pipeline Development, and Hyperparameter Tuning

© The Author(s), under exclusive license to APress Media, LLC, part of Springer Nature 2021

T. C. NokeriData Science Revealedhttps://doi.org/10.1007/978-1-4842-6870-4_7

7. Finding Hyperplanes Using Support Vectors

Tshepo Chris Nokeri¹  

(1)

Pretoria, South Africa

 

The preceding chapter presented a linear classification model called linear discriminant analysis (LDA), which distributes groups equally when covariance matrices are equivalent. Although the classifier is one of the optimum linear classification models, it has its limits. Foremost, we cannot estimate the dependent variable using a categorical variable. Second, we train and test the model under strict assumptions of normality. This chapter brings together an alternative linear classification ...