You can create Machine Learning models from scratch or from templates
The template is the best approach to begin creating your machine learning model. It allows us to create a machine learning model based on commonly observed problems, for example the MLT.
Actually Tiki only support one template :
The MLT template solves the problems associated with suggesting similar content (finds documents that are "like" a given set of documents).
This emulates Module More Like This
More info: https://github.com/RubixML/RubixML/issues/75
|Transformers and Applied Learners||Arguments|
|WordCountVectorizer||maxVocabulary :1000 , minDocumentFrequency :1 ,maxDocumentFrequency: 500 ,okenizer :default|
|BM25Transformer||alpha :1.2 , beta :0.75|
|KDNeighbors||k:20, weighted:true, tree : BallTree|