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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