hi. I tried to figure out how you calcualte pearson correlation, but it looks like you use this formula:
sumXY / sqrt(sumX2 * sumY2) where sumXY = sumXY - meanY * sumX; sumX2 = sumX2 - meanX * sumX; sumY2 = sumY2 - meanY * sumY; i don't really understand how you got these equations. could you explain it to me? I thought pearson correlation would be like this E(x_i-meanX)(y_i-meanY) / sdX*sdY for my project I would need to get sample correlation coefficient which would be something like this: sum(x_i-meanX)(y_i-meanY)/(N-1) thanks a lot. srowen wrote: > > Yes. Look at PearsonCorrelationSimilarity. It implements > ItemSimilarity so it can compute a Pearson correlation between ratings > for two items. Pearson is the covariance divided by the product of the > standard deviations. So, just multiply the similarity value you get by > the standard deviations of the items' preference values. > > The variance of each item's preference values is simply the square of > the standard deviation, if that's what you mean. > > You can use RunningAverageAndStdDev to help compute standard deviation > if you like. > > On Thu, Nov 26, 2009 at 3:14 PM, jamborta <[email protected]> wrote: >> >> hi guys, >> just wondering if you have a method implemeted which would calculate the >> covariance between two items. and the variance of an item. I looked >> itemSimilarities but that one does something different. >> >> thanks >> Tama >> -- >> View this message in context: >> http://old.nabble.com/Mahout-Taste-covariance-between-two-items-tp26530825p26530825.html >> Sent from the Mahout User List mailing list archive at Nabble.com. >> >> > > -- View this message in context: http://old.nabble.com/Mahout-Taste-covariance-between-two-items-tp26530825p26535849.html Sent from the Mahout User List mailing list archive at Nabble.com.
