<p>Please take a look at this proposal: <a href="http://area51.stackexchange.com/proposals/7607?tab=ontopic&amp;phase=definition#tab-top"><strong>Machine Learning > On Topic</strong></a></p>

<p>I would like your opinion if these on-topic questions would be welcomed on this site:</p>

<ul>
<li>I am using a neural network with the backpropagation algorithm. How can I calculate significance of each input variable on the output?</li>
<li>What is the best software for performing Gaussian Process regression?</li>
<li>What is the best R package to use for support vector machines (SVMs)?</li>
<li>Given a dataset, how do I determine the best ratio of training to test data for a supervised learning algorithm?</li>
<li>Generally, when are Hessian-based optimization methods preferable to first order methods?</li>
<li>If I have an undirected, tree-structured model, what's the most efficient way to pull an exact sample from its distribution?</li>
<li>Why does the kernelized support vector machine algorithm care that the kernel function be positive semi-definite? What happens if it isn't?</li>
</ul>

<p>If they are consistently on-topic, I will be closing that proposal as a duplicate and inviting those users to Stats.stackexchange.</p>
