Is SVM a good choice for this imputing a numerical variable?

Let's say I have 10,000 training points, 100,000,000 points to impute, and 5-10 prediction variables/parameters, all numeric (for now). The target variable is numeric, skewed normal with outliers. I want to use SVM, but I'm new, so I would appreciate any opinions.

Topic non-parametric data-imputation svm algorithms

Category Data Science

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