Releases: dkpro/dkpro-tc
DKPro TC 1.0.2
dkpro-tc-1.0.1
Bugfixes for details see here: #488
dkpro-tc-1.0.0
dkpro-tc-0.9.0
Highlights
Issue 358: Speed up sequence tagging by using sparse-feature mode as default
Issue 355: Make document mode to a special case of unit mode
Issue 353: Enable passing CollectionReaderDescriptions instead of defining reader dimensions
Issue 341: Improve DKPro-TC preprocessing speed by removing CasMultiplier from Workflow
Issue 293: Add mavenized libsvm as machine learning adapter
Issue 50: Create a dedicated evaluation object/module
Issue 39: Multiple instances of the same feature extractor with different configurations should be possible
Major Version Enhancements
DKPro Lab 0.13.0
DKPro Core 1.8.0
Meka 1.9.0
Other Issues Fixed
Issue 363: Extend basic-implementation of Liblinear
Issue 367: CRFsuite: Enable full parametrization
Issue 366: Unify parametrization of SVM modules
Issue 361: Refactor ValidityCheckConnector (Pre/Post)
Issue 207: Potential severe problem with ngram meta collectors and extractors
DKPro-TC 0.8.0 Release
Highlights
Issue 223: Add support for model load/save on Weka/CRFsuite
Issue 282: Model saving/loading of SVMHMM models
Issue 296: Adding save-model TaskBase to TCMachineLearningAdapter
Major Version Enhancements
DKPro Lab 0.12.0
DKPro parent pom 13
Java 8
Other Issues Fixed
Issue 239: SVMhmm is missing OSx binary
Issue 269: Replace @author annotation in source by a contributors.txt file
Issue 295: Setting NoOpAnnotator by default if no preprocessing is defined
Issue 305: CRFSuite binary: Windows 64 bit binary is missing
Issue 321: Update package names to org.dkpro.tc
Issue 326: Example Project: Prefixing examples with the MLA name that is used
dkpro-tc-0.7.0
DKPro TC 0.7.0-Release
Highlights
- Issue 183: support for CRFsuite machine learning framework
- Issue 190: Support for SVMhmm machine learning framework
- Issue 126: new generic machine learning module dkpro-tc-ml, new functionality to set a machine learning adapter
- Issues 199, 200: New functionality to set the feature store, new sparse feature store
Enhancements
- Additional demos for new machine learning frameworks and other experiment setups
- New module dkpro-tc-evaluation for cross-framework evaluation functionality (not fully supported yet, only works for single-label learning mode)
Major Version Enhancements
- Upgrade to DKPro Core 1.7.0 / DKPro parent pom 10
- Upgrade to Weka 3.7.11
- Upgrade to Meka 1.7.3
Other Issues Fixed
- Issue 220: Fixed wrong calculation of label-wise scores in multi-label learning mode
- Issue 163: SimpleDkproTCReader does not allow to set language
- Issue 139: Experiments should fail with a meaningful exception if no data are found
- Issue 160: Invalid column index in reports which produce XLS files
- Issue 175: ValidityCheckTask only verifies the experiment setup based on training data
Other
- Module de.tudarmstadt.ukp.dkpro.tc.features.pair.similarity-asl has been excluded from the Maven Central release, since the "DKPro Similarity" dependency is not yet available on Central.
- All demos in dkpro-tc-examples and dkpro-tc-examples-groovy now have unit tests.
- dkpro-tc-ml-mallet is deprecated and will be removed from the next release due to a lack of support.