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

What is a non-linear support vector machine?Question 10Answera.A support vector machine that is sensitive to the scale of the input variablesb.A support vector machine that uses a non-linear kernel functionc.A support vector machine that is sensitive to the presence of outliersd.A support vector machine that uses a linear kernel function

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

What is a multi-class support vector machine?Question 11Answera.A support vector machine that can handle multiple classes of datab.A support vector machine that can handle data with a high number of dimensionsc.A support vector machine that uses a non-linear kernel functiond.A support vector machine that uses a linear kernel function