Which machine learning technique could be for training on a vector of inputs from 0 to 1 to a target …

Which machine learning technique could be for training on a vector of inputs from 0 to 1 to a target output ranging from 0 to 100? I have a matrix where each row is a vector of numbers from 0 to 1 and each column corresponds to a predictor. I have a separate column vector where each row value corresponds to the target value of the observation from the row in the aforementioned matrix. e.g. observations = [.2 .6 .3 .7 .1; .1 .2 .6 .9 .5; etc] targets = [35.9; 57.1; etc] I’ve tried a polynomial and sigmoid fit for the data but they don’t fit well so I wanted to try a machine learning approach. I originally wanted SVM but found that can’t be used for non-binary target…


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