History: Machine Learning Models

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You can create ((Machine Learning)) models from scratch or from templates

!! 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.
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!! Available Templates
 Actually Tiki only support one template :

!! More Like This (MLT)
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 Learners for MoreLikeThis

{FANCYTABLE(head="__Transformers and Applied Learners__|__Arguments__" sortable="n")}
TextNormalizer | 
StopWordFilter | 
WordCountVectorizer| maxVocabulary :1000 , minDocumentFrequency :1 ,maxDocumentFrequency: 500 ,okenizer :default
BM25Transformer | alpha :1.2 , beta :0.75
KDNeighbors | k:20, weighted:true, tree : BallTree
{FANCYTABLE}

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