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From "Andres R. Masegosa " <and...@cs.aau.dk>
Subject Convergence Criterion in IterativeDataSet
Date Fri, 04 Sep 2015 12:25:53 GMT

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?


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