About: Aika is an open source text mining engine. It can automatically extract and annotate semantic information in text. In case this information is ambiguous, Aika will generate several hypothetical interpretations about the meaning of this text and retrieve the most likely one.

Aika Version 0.17 2018-05-14

• Introduction of synapse relations. Previously the relation between synapses was implicitly modeled through word positions (RIDs). Now it is possible to explicitly model relations like: The end position of input activation 1 equals to the begin position of input activation 2. Two types of relations are currently supported, range relations and instance relations. Range relations compare the input activation range of a given synapse with that of the linked synapse. Instance relations also compare the input activations of two synapses, but instead of the ranges the dependency relations of these activations are compared.
• Removed the norm term from the interpretation objective function.
• Introduction of an optional distance function to synapses. It allows to model a weakening signal depending on the distance of the activation ranges.
• Example implementation of a context free grammar.
• Example implementation for co-reference resolution.
• Work on an syllable identification experiment based on the meta network implementation.

Aika Version 0.15 2018-03-16

• Simplified interpretation handling by removing the InterpretationNode class and moving the remaining logic to the Activation class.
• Moved the activation linking and activation selection code to separate classes.
• Ongoing work on the training algorithms.

About: glyph is a python 3 library based on deap providing abstraction layers for symbolic regression problems.

Initial Announcement on mloss.org.

About: Code for Calibrated AdaMEC for binary cost-sensitive classification. The method is just AdaBoost that properly calibrates its probability estimates and uses a cost-sensitive (i.e. risk-minimizing) decision threshold to classify new data.

Updated license information

About: General purpose Java Machine Learning library for classification, regression, and clustering.

See github release tab for change info

About: Learning M-Way Tree - Web Scale Clustering - EM-tree, K-tree, k-means, TSVQ, repeated k-means, clustering, random projections, random indexing, hashing, bit signatures

Initial Announcement on mloss.org.