<html>
<head>
<meta http-equiv="Content-Type" content="text/html; charset=us-ascii">
</head>
<body style="word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space; color: rgb(0, 0, 0); font-size: 14px; font-family: Calibri, sans-serif;">
<div>I would like to train a neural net (or similar classifier) to predict one probabilistic value from 9 principal components. When I do it in R (using nnet) it caps at a few hundred observations, but that seems too small a sample when I have over 40k cases.
I know that the space of machine learning algorithms (distributed and otherwise) is vast and so was wondering if there was something that the StarCluster community might recommend. (Ideally it would be something that I could set up on StarCluster with minimal
difficulty.)</div>
<div><br>
</div>
<div>Thanks in advance,</div>
<div><a name="_MailAutoSig" style="font-size: 15px;">-Alessandro Gagliardi</a></div>
</body>
</html>