Function Configuration

A function configuration object is used to create or load a function.

It is a JSON object that looks like this:

  "id": <id>, 
  "type": <type>, 
  "params": { 

Not all three of these fields are required in all contexts:

The following types of functions are available:

classifierApply a trained classifier to new data[doc]
classifier.explainExplain the output of a classifier[doc]
embedding.neighborsReturn the nearest neighbors of a known row in an embedding dataset[doc]
feature_hasherFeature hashing feature generator[doc]
fetcherFetches the contents of a URL each time it's invoked[doc]
http.useragentParse user agent strings into their components[doc]
image.proximatevoxelsFind values in a cubic volume inside a 3d embedding[doc]
image.readpixelsWraps access to a 2d embedding[doc]
kmeansApply a k-means clustering to new data[doc]
mongodb.queryTakes a MongoDB query, forwards it to MongDB, parses the result and returns it as an MLDB result.[doc]
poolingApply a pooling function[doc]
probabilizerApply a probability calibration model[doc]
sql.expressionRun an SQL expression as a function[doc]
sql.queryRun a single row SQL query against a dataset[doc]
statsTable.bagOfWords.posnegGet the pos/neg p(outcome)[doc]
statsTable.getCountsGet stats table counts for a row of keys[doc]
stemmerApply a stemming algorithm column names[doc]
stemmerdocApply a stemming algorithm on a single document[doc]
svd.embedRowApply a trained SVD to embed a row into a coordinate space[doc]
tensorflow.graphGraph parameters for a trained TensorFlow model[doc]
tfidfApply a TF-IDF scoring to a bag of words[doc]
tokensplitInsert spaces after tokens from a dictionary[doc]

See also