About: A thin Python3 wrapper that uses the javabridge Python library to communicate with a Java Virtual Machine executing Weka API calls.

• upgraded to Weka 3.9.2
• properly initializing package support now, rather than adding package jars to classpath
• added weka.core.ClassHelper Java class for obtaining classes and static fields, as javabridge only uses the system class loader

About: A thin Python wrapper that uses the javabridge Python library to communicate with a Java Virtual Machine executing Weka API calls.

• upgraded to Weka 3.9.2
• properly initializing package support now, rather than adding package jars to classpath
• added weka.core.ClassHelper Java class for obtaining classes and static fields, as javabridge only uses the system class loader

About: The Advanced Data mining And Machine learning System (ADAMS) is a flexible workflow engine aimed at quickly building and maintaining data-driven, reactive workflows, easily integrated into business processes.

Some highlights:

• Code base was moved to Github
• Nearly 90 new actors, 25 new conversions
• much improved deeplearning4j module
• experimental support for Microsoft's CNTK deep learning framework
• rsync module
• MEKA webservice module
• improved support for image annotations
• improved LaTeX support
• Websocket support

About: KeplerWeka represents the integration of all the functionality of the WEKA Machine Learning Workbench into the open-source scientific workflow Kepler. Among them are classification, [...]

• Now compatible with Kepler 2.0
• New version of WEKA included (patched 3.7.2 release), WEKA's new package manager works in conjunction with Kepler
• Renamed actor Count to ConditionalTee, introduced new Count actor
• Removed actors OutputLogger, MultiSync, TwinSync

About: BenchMarking Via Weka is a client-server architecture that supports interoperability between different machine learning systems. Machine learning systems need to provide mechanisms for processing [...]

Initial Announcement on mloss.org.