@@ -35,8 +35,8 @@ PUT _ml/anomaly_detectors/example1
3535 "analysis_config": {
3636 "detectors": [{
3737 "function" : "lat_long",
38- "field_name" : "transactionCoordinates ",
39- "by_field_name" : "creditCardNumber "
38+ "field_name" : "transaction_coordinates ",
39+ "by_field_name" : "credit_card_number "
4040 }]
4141 },
4242 "data_description": {
@@ -49,22 +49,23 @@ PUT _ml/anomaly_detectors/example1
4949
5050If you use this `lat_long` function in a detector in your {anomaly-job}, it
5151detects anomalies where the geographic location of a credit card transaction is
52- unusual for a particular customer’s credit card. An anomaly might indicate fraud.
52+ unusual for a particular customer’s credit card. An anomaly might indicate
53+ fraud.
5354
54- IMPORTANT: The `field_name` that you supply must be a single string that contains
55- two comma-separated numbers of the form `latitude,longitude`, a `geo_point` field,
56- a `geo_shape` field that contains point values, or a `geo_centroid` aggregation.
57- The `latitude` and `longitude` must be in the range -180 to 180 and represent a
58- point on the surface of the Earth.
55+ IMPORTANT: The `field_name` that you supply must be a single string that
56+ contains two comma-separated numbers of the form `latitude,longitude`, a
57+ `geo_point` field, a `geo_shape` field that contains point values, or a
58+ `geo_centroid` aggregation. The `latitude` and `longitude` must be in the range
59+ -180 to 180 and represent a point on the surface of the Earth.
5960
6061For example, JSON data might contain the following transaction coordinates:
6162
6263[source,js]
6364--------------------------------------------------
6465{
6566 "time": 1460464275,
66- "transactionCoordinates ": "40.7,-74.0",
67- "creditCardNumber ": "1234123412341234"
67+ "transaction_coordinates ": "40.7,-74.0",
68+ "credit_card_number ": "1234123412341234"
6869}
6970--------------------------------------------------
7071// NOTCONSOLE
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