number of training documents for classifier what is the difference between data points of training does the distribution of training records improve the success of the test? how much data for in-sample classification how is the distribution of training data related to text classification does having an equal number of training documents improve my classification success? how does a disparity in number of training documents affect classifiers how does the size of a training document influence text class? how does data consistency affect classifiers do training documents impact text classification what does a dispersed training document mean how does a disparity in the number of training documents affect text classification? which of the following relates to the number of training documents for a classifier? what is the difference between a training data point and an out of sample data point? how does a uniform distribution of training documents affect text classification? how does data distribution affect classifier performance how does data in a sample affect classification when using a training data set how does this affect the classifying success what is the difference between a distribution of training documents and a training classifier? how do the numbers of training documents affect classification