# How to calculate confidence interval of regression algorithms?

I am looking for ways to calculate confidence interval of the prediction given by the following algorithms:

1. Support Vector Regression
2. K-Nearest Neighbor Regression
3. Random Forest Regression
4. Polynomial Regression (Polynomial Features in scikit-learn followed by Linear Regression)

Just to clarify, suppose $\hat{y}$ is the estimate of $y$, where $y$ is the output variable and $x = [x_1, x_2, x_3,...,x_N]$ is the input variable. I would like to get the confidence interval of $\hat{y}$ from the above algorithms.

So far, I have found the followings:

1. Bootstrapping confidence interval from a regression prediction
2. CONFINE & CONFIVE: article can be downloaded here.

I am new to this topic and looking for a comprehensive list of alternatives with pros and cons.