Hi, Probably your data is multi-target and not multi-label so it is only using the multi-target metrics. As the target variables are thus not binary, only results for a restricted set of metrics can be produced. Although it could be argued that Precision, Recall and F1 scores may be applied also in multi-target evaluation, this is not currently implemented in Meka. Jesse
Unknown Values in Output Vectors Become 0 When Evaluating
update for new release
MEKA CODE REPOSITORY HAS NOW MOVED TO: https://...
Final update to README, version number
Markdown fixed in README
Delete README.txt (has been replaced by README.md)
README updated; changed from txt to markdown fo...
Renamed Show*PrecisionRecall to, more generical...
Minor update to tutorial
New ref files from tests
Update .ref files from tests
Tidy up SCC and supporting code
Updated version number, prepared for next release
Updated tutorial, and included new screenshots.
Reorganized tutorial (section 4); added Explore...
Updated README with recent developments
Added threshold data and visualization plugin f...
Added Macro-Average PRC, and Macro and Micro Pr...
Added flatten() method for double[][] matrices ...
Added a visualization plugin to show micro-aver...
Added Micro-averaged Curve data to Results
Added method for getting a micro-averaged curve
Added 'average rank' row
More efficient implementation of some Metrics
Mentioned that high -verbosity will cause extra...
Bug fix for obtaining ranking matrix.
CT prepares a default chain in the same way as CC
Added methods to obtain Value and Rank matrices...
Added method for Nemenyi test (not yet implemen...
Fixed bug in log statement: folds numbered from...
Nicer production of Latex output
Added multitarget version of RAkELd, which shar...
Fixed RAkELd, wrt earlier modifications to PSUtils
SCC now extends NSR, makes more use of existing...
update to NSR
Refactor some super-label utils, and moving som...
Fixed bug where attempted to apply threshold wh...
Latest improvements mentioned in README
Result class now contains getAvailableMetrics(....
Finished SaveCSV plugin for incremental evaluat...
Training dataset should not be required again i...
Using setMeasurement(String,Object), getMeasure...
Using setMeasurement(String,Object),getMeasurem...
Plugin to save output as CSV file
Bug fix regarding getK() method
Bug fix in table output
RakEL now extends RakELd, and not the other awy...
Nicer Latex output from experiments.
Add Latex class for Latex output frome experime...
Add LatexMeasurement class for providing latex ...
Variables linked to options should not be chang...
CDT now interprets '0' width like CT.
For CT, allow width of 0 to indicate width of L...
Added Levenshtein distance to multi-target metr...
Update tutorial explaining prequential vs batch...
Cleanup of Results class; renaming/adding methods.
Samples option is also Batches option for batch...
Restored and fixed 'batch-incremental' evaluation.
Editions to tutorial
Added old batch-incremental option for incremen...
Tutorial updated regarding recent changes
Command-line options fixed, change to 'supervis...
Updated README with recent changes
Improve evaluation command-line help text
More revision of the Tutorial
New material, highlighting points which need at...
Incremental samples now include #Instances, #Sa...
Add note about averaging when type endsWith 'CV'
DeepML takes a MultiLabel base classifier
Fixed MCC 'inferenceIterations' option and tooltip
Update tutorial
update javadoc comments and outline future dev ...
MajorityLabelset is multi-target capable.
Restore multi-target incremental eval; display ...
Fixed bug in BPNN (Random number generator not ...
Added flag to allow for more memory to java
Fixed bug causing exception on labelsets.
Test/train time calculated correctly (cumulativ...
Option for number-of-samples becomes -x
PrequentialEvaluation now includes Instances wi...
'number of folds' determines number of samples ...
code cleanup
set/get methods and tool tips added/cleaned up;...
Added tooltips, cleaned up options code
AbstractNeuralNet implements Randomizable
Fixed tip text methods
Added set/get methods, tip text
made note of recent changes
A fresh initial look at the experimenter
Cleaned up options and tool tips
Fixed crash where empy labelset appears in dist...
Introduce AbstractMultiLabelClassifier, e.g., M...
setUnlabelledData renamed introduceUnlabelledDa...
setChain(..) renamed to prepareChain(..)
Cleaned up false javadoc flags
Payoff option (-P) set by String and uses any M...
MCC now uses CC's prepareChain method.
Update log of recent changes
Removed debug output