Hi Peter,
thanks for your answer, I'll be waiting for the added feature, thanks.
I'm implementing some machine learning stuff and i would find it useful for computing mean squared loss to use the pointwise pow, or for l2 regularization like in matlab:
sum(theta(2:end).^2))
there are probably other ways to do it, but this seems natural to me.
Also the log and exp functions will help me in implementing the sigmoid function for neural networks and logistic regression and the logistic regression cost function like the matlab ones:
function g = sigmoid(z)
g = 1 ./ (1 + exp(-z));
end
J = ((1/m) * sum(- y .* log(sigmoid(X * theta)) - (1 - y) .* log(1 - sigmoid(X * theta)))) + ((lambda/(2*m)) * sum(theta(2:end).^2));
Hope this helps to understand the use case for thos functions.