Polynomial Kernels
In machine learning, a kernel function is a mathematical function that transforms data into a higher-dimensional space, allowing for non-linear classification or regression. Polynomial kernels are a type of kernel function that use a polynomial function to map the data into a higher-dimensional space. The degree of the polynomial determines the degree of the mapping, and higher degrees can capture more complex relationships between the data. Polynomial kernels are commonly used in support vector machines (SVMs) for classification tasks, as they can effectively separate non-linearly separable data. However, higher degrees can lead to overfitting, so the degree of the polynomial must be carefully chosen to balance model complexity and accuracy.
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