On Thu, Oct 13, 2011 at 11:10 PM, Robert Layton <[email protected]> wrote: > I'm working on adding Adjusted Mutual Information, and need to calculate the > Mutual Information. > I think I have the algorithm itself correct, except for the fact that > whenever the contingency matrix is 0, a nan happens and propogates through > the code. >
FWIW, scipy.stats defines entropy of p(x) = 0 to be 0, and I think it is so by definition. The other option I've seen in software is to let the user define the eps. https://github.com/scipy/scipy/blob/master/scipy/stats/distributions.py#L5284 > Sample code on the net [1] uses an eps=np.finfo(float).eps. Should I do > this, adding eps to anything that is a denominator or parameter to log? > Is there a better way? > [1] http://blog.sun.tc/2010/10/mutual-informationmi-and-normalized-mutual-informationnmi-for-numpy.html > FYI: My current code: > def mutual_information(labels_true, labels_pred, contingency=None): > if contingency is None: > labels_true, labels_pred = check_clusterings(labels_true, > labels_pred) > contingency = contingency_matrix(labels_true, labels_pred) > # Calculate P(i) for all i and P'(j) for all j > pi = np.sum(contingency, axis=1) > pi /= float(np.sum(pi)) > pj = np.sum(contingency, axis=0) > pj /= float(np.sum(pj)) > # Compute log for all values > log_pij = np.log(contingency) > # Product of pi and pj for denominator > pi_pj = np.outer(pi, pj) > # Remembering that log(x/y) = log(x) - log(y) > mi = np.sum(contingency * (log_pij - pi_pj)) > return mi > -- > > > My public key can be found at: http://pgp.mit.edu/ > Search for this email address and select the key from "2011-08-19" (key id: > 54BA8735) > Older keys can be used, but please inform me beforehand (and update when > possible!) > > > ------------------------------------------------------------------------------ > All the data continuously generated in your IT infrastructure contains a > definitive record of customers, application performance, security > threats, fraudulent activity and more. Splunk takes this data and makes > sense of it. Business sense. IT sense. Common sense. > http://p.sf.net/sfu/splunk-d2d-oct > _______________________________________________ > Scikit-learn-general mailing list > [email protected] > https://lists.sourceforge.net/lists/listinfo/scikit-learn-general > > ------------------------------------------------------------------------------ All the data continuously generated in your IT infrastructure contains a definitive record of customers, application performance, security threats, fraudulent activity and more. Splunk takes this data and makes sense of it. Business sense. IT sense. Common sense. http://p.sf.net/sfu/splunk-d2d-oct _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
