Hi,
I trying to implement some machine learning algorithms that involve several iterations until convergence (to a fixed point). My idea is to use a IterativeDataSet with an Aggregator which produces the result (i.e. a set of parameters defining the model). >From the interface "ConvergenceCriterion", I can understand that the convergence criterion only depends on the result of the aggregator in the current iteration (as happens with the DoubleZeroConvergence class). However, it is more usual to test convergence by comparing the result of the aggregator in the current iteration with the result of the aggregator in the previous iteration (one usually stops when both results are similar enough and we have converged to a fixed point). I guess this functionality is not included yet. And this is because the convergence criteria of flink implementations of K-Means and Linear Regression is to stop after a fixed number of iterations. Am I wrong? Regards Andres
