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What is the time complexity of training a support vector machine? Follow-ups: Time complexity of inference in SVM. Time complexity (both for training and inference) with depending on Kernel (Linear, RBF).

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  • What is the time complexity of training a support vector machine? Follow-ups: Time complexity of inference in SVM. Time complexity (both for training and inference) with depending on Kernel (Linear, RBF).
  • How would you describe the time complexity characteristic of SVM training? Can you describe the time complexity for the inference phase in SVMs? Can you compare the time complexities for training and inference in SVMs with linear and RBF kernels?
  • What are the factors that determine the time complexity of SVM training? How does the time complexity during SVM inference compare to its training time complexity? What are the time complexity implications of using different kernels like Linear and RBF in SVMs?
  • Can you outline the algorithmic time complexity for training a support vector machine? What would you estimate the time complexity to be for an SVM during the inference stage? How do Linear and RBF kernels influence the computational time complexity of SVMs?
  • How does the training time complexity of SVMs scale with the size of the dataset? How resource-intensive is the inference operation in a support vector machine in terms of time complexity? What impact do Linear and RBF kernels have on the training and inference time complexity of SVM models?
  • What can you tell me about the efficiency of SVM training in terms of time complexity? Could you explain the time efficiency of inference with a trained SVM model? Could you describe how kernel selection (Linear vs RBF) affects the time complexity of SVMs?
  • How computationally intensive is it to train a support vector machine? What computational cost is involved in SVM prediction in relation to time complexity? In terms of time complexity, how does the use of Linear or RBF kernels in SVMs differ?
  • What is the big-O notation for the time complexity of an SVM training process? What governs the time complexity when an SVM model is deployed for making predictions? How does the computational demand vary for SVMs with Linear versus RBF kernels during training and inference?
  • How does the size of the input data affect the time complexity of training an SVM? How is the time complexity for SVM inference calculated? Can you explain the effect of different kernels on the time complexity of SVMs?
  • What time complexity considerations are there when training a support vector machine?
  • Could you discuss the computational complexity involved in training an SVM? What is the time complexity associated with making predictions using a trained SVM? How does the choice of kernel in an SVM affect the time complexity for both training and inference?

Interview question asked to Data Scientists interviewing at OfferUp, Shopee, Grubhub and others: What is the time complexity of training a support vector machine? Follow-ups: Time complexity of inference in SVM. Time complexity (both for training and inference) with depending on Kernel (Linear, RBF)..