Procedure Configuration

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

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 procedures are available:

classifier.experimentTrain and test a classifier[doc]
classifier.testCalculate the accuracy of a classifier on held-out data[doc]
classifier.trainTrain a supervised classifier[doc]
export.csvExports a dataset to a target location as a CSV[doc]
import.gitImport a Git repository's metadata into MLDB[doc]
import.jsonImport a text file with one JSON per line into MLDB[doc]
import.sentiwordnetImport a SentiWordNet file into MLDB[doc]
import.textImport from a text file, line by line.[doc]
import.word2vecImport a word2vec file into MLDB[doc]
kmeans.trainSimple clustering algorithm based on cluster centroids in embedding space[doc]
meltPerforms a melt operation on a dataset[doc]
mongodb.importImport a dataset from MongoDB[doc]
permuter.runRun a child procedure with permutations of its configuration[doc]
probabilizer.trainTrains a model to calibrate a score into a probability[doc]
randomforest.binary.trainTrain a supervised binary random forest[doc]
statsTable.bagOfWords.trainCreate statistical tables of trials against outcomes for bag of words[doc]
statsTable.trainCreate statistical tables of trials against outcomes[doc]
summary.statisticsCreates a dataset with summary statistics for each columns of an input dataset[doc]
svd.trainTrain a SVD to convert rows or columns to embedding coordinates[doc]
tfidf.trainPrepare data for a TF-IDF function[doc]
transformApply an SQL expression over a dataset to transform into another dataset[doc]
tsne.trainProject a high dimensional space into a low-dimensional space suitable for visualization[doc]

See also