Comments (3)
Hi Vincenzo,
I will take a look at it as soon as possible. Can you tell us how you are calling the precision and recall metrics? If you are using your code, it will be useful to know how you are creating and printing the metrics. If you are using a script, it would also be helpful to know the commands you are using.
Thanks,
Alejandro
from rival.
yes sure, This is my code:
....
SimpleParser sp = new SimpleParser();
DataModel dm = sp.parseData(new File("path_of_my_predictions_file"));
DataModel dmtest = sp.parseData(new File("path_of_my_test_file"));
Precision pr = new Precision(dm, dmtest);
pr.compute();
System.out.println(pr.getValue());
Recall rc = new Recall(dm, dmtest);
rc.compute();
System.out.println(rc.getValue());
....
from rival.
Hi Vincenzo, sorry it took so long, but I thought it was going to be something related with how you called the metrics, so I needed to prepare a test case. In the end, the problem seems to be with your definition of precision (and recall): instead of using the definition from the classification literature, you should look at the one used in information retrieval (here), where the total number of retrieved documents are considered in the denominator. In your case, this means: 12 (positive) / 22 (retrieved) = 0.54.
Let me know if you have any comments,
Alejandro
from rival.
Related Issues (20)
- Check evaluation metrics are suitable for unary/binary data
- Check splitters are suitable for unary/binary data
- Check parsers are suitable for unary/binary data
- Not generalized DataModel for RandomSplitter class
- Not generalized DataModel for Temporal Splitter class
- Not generalized DataModel for SplitterRunner class
- Using Examples with a dataset like ML-10M HOT 11
- Update license snippet in gh-pages HOT 1
- Create jar file of 0.3-SNAPSHOT to be used outside eclipse HOT 2
- DataModel does not support duplicate ratings in dataset
- Implement RecSys Challenge 2016 metric
- [Question]: Split dataset in training, validation and test HOT 12
- Missing documentation for unsupported combination in RandomSplitter HOT 3
- Add custom behaviour to DataModelUtils.saveModel HOT 3
- [Question] Maven install command HOT 5
- Bug in CrossValidatedMahoutKNNRecommenderEvaluator
- Type mismatch: cannot convert from CSVParser to Iterable<CSVRecord> HOT 11
- Test coverage HOT 3
- Precision values are not consistent with those from other ranking metrics
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