# ANALYZE¶

Syntax:

ANALYZE 'data' BY MODEL model_name USING method_name


Examples:

jubaql> ANALYZE '{"name": "慶喜"}' BY MODEL cls USING classify
{
"predictions":[{
"label":"徳川",
"score":0.05624999850988388
},{
"label":"北条",
"score":0.0
},{
"label":"足利",
"score":0.0
}]
}

jubaql> ANALYZE '荻野貴司' BY MODEL reco USING complete_row_from_id
{
"string_values":{
},
"num_values":{
"長打率":0.34623855352401733,
"試合数":102.7064208984375,
"打数":325.32110595703125,
"安打":84.64220428466797,
"RC27":3.8101837635040283,
"出塁率":0.3158532977104187,
"OPS":0.6621102094650269,
"盗塁":6.31192684173584,
"打率":0.25398167967796326,
"四球":27.706422805786133,
"打席":367.9449462890625,
"打点":31.302751541137695,
"併殺打":6.2110090255737305,
"犠打":9.2660551071167,
"死球":3.4770641326904297,
"三振":54.40367126464844,
"本塁打":4.917431354522705,
"XR27":3.7999088764190674
}
}


## Explanation¶

ANALYZE queries a previously defined and trained Jubatus model for results of the learning process.

• data is a string that will become the parameter of the given Jubatus method. When this parameter is a datum, data is expected to be a JSON string and will be converted to a datum using the columns specified in the WITH clause of the CREATE MODEL statement.
• model_name is the name of a model previously defined using CREATE MODEL. (For the returned value to make any sense, that model should have also been trained using the UPDATE MODEL statement.)
• method_name is the method to use for analyzing the model:
• calc_score for an ANOMALY model,
• classify for a CLASSIFIER model,
• complete_row_from_id or complete_row_from_datum for a RECOMMENDER model.

## Notes¶

• The results will be returned as JSON corresponding to each method’s return type.