Which kernel can be used in scikit-learn's SVM implementation?Answer areaLinearPolynomialRadial Basis Function (RBF)All of the above

What kernel can be used in SVM to handle non-linear data?Answer areaLinear KernelPolynomial KernelRadial Basis Function (RBF) KernelAll of the above

Which kernel function is commonly used in a Support Vector Machine Classifier when dealing with non-linearly separable data?Review LaterLinear KernelPolynomial KernelRadial Basis Function (RBF) KernelSigmoid Kernel

What is a kernel function in the context of support vector machines?Question 3Answera.A function that computes the distance between the input data and the support vectorsb.A function that optimizes the margin maximization problemc.A function that predicts the class labels of the input datad.A function that maps the input data into a higher-dimensional space

Which Python library is commonly used for implementing Support Vector Machines (SVM)?Answer areapandasscikit-learnNumpyTensorFlow

Which of the following is a disadvantage of SVM?Answer areaIt works well with high-dimensional dataIt is sensitive to the choice of kernel and regularization parameterIt can handle both linear and non-linear dataIt has a clear geometric interpretation