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in one hot encode , there is no need count and filte when the threshold less than 1.
code is : DataSet<Tuple3<Integer, String, Long>> countTokens = StringIndexerUtil.countTokens(inputRows, true) .filter(new FilterFunction<Tuple3<Integer, String, Long>>() { @OverRide public boolean filter(Tuple3<Integer, String, Long> value) { return value.f2 >= thresholdArray[value.f0]; } });
The text was updated successfully, but these errors were encountered:
Thanks, we'll optimize it later.
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Remove the filter in onehot train op when the threshold less than 1. …
3466b1b
…see #112.
lqb11
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in one hot encode , there is no need count and filte when the threshold less than 1.
code is :
DataSet<Tuple3<Integer, String, Long>> countTokens = StringIndexerUtil.countTokens(inputRows, true)
.filter(new FilterFunction<Tuple3<Integer, String, Long>>() {
@OverRide
public boolean filter(Tuple3<Integer, String, Long> value) {
return value.f2 >= thresholdArray[value.f0];
}
});
The text was updated successfully, but these errors were encountered: