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lachlandeer
Hi @lachlandeer , I've updated the SVM article as per your request (#1124), specifically focusing on enhancing the explanations of key concepts. Previously, the article had a lot of code blocks, so I've added two new sections to explain the concepts: 'Large-margin Classification' briefly defines the margin and support vectors, while 'Choosing the Right SVM Kernel' offers practical tips on kernel selection.
In addition to these sections, I've provided explanations on similarity functions, also known as kernels, and briefly touched on the impact of hyperparameters C and Gamma on model performance. To aid understanding, I've included images clarifying these concepts.
While the code remains largely unchanged, I've integrated the 'training and test data' code with the modeling code.
Overall, these updates add around two minutes of reading time to the article."