Predictions on training set shorter than training set
Are there missing values in your data? If so, try adding the argument na.action = na.exclude to your original call to glm or lm. It is like the default na.omit except that it records which rows were omitted (because they contained missing values) and fills in the corresponding entries in the predictions, residuals, etc. with NA's. You can also set options(na.action = "na.exclude") to make it the default na.action in lm() and similar functions. Bill Dunlap TIBCO Software wdunlap tibco.com On Thu, Apr 23, 2015 at 10:23 AM, Mark Drummond <mark at markdrummond.ca> wrote:
Hi all, Given a simple logistic regression on a training data set using glm, the number of predicted values is less than the number of observations in the training set:
fit.train.pred <- predict(fit, type = "response") nrow(train)
[1] 62660
length(fit.train.pred)
[1] 58152
As a relative newcomer, I've run lots of simple glm, CART etc. models but this is the first time I have seen this happen. Is this a common issue and is there a fix? An option to predict() perhaps? -- Cheers, Mark Mark Drummond mark at markdrummond.ca When I get sad, I stop being sad and be Awesome instead. TRUE STORY.
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