@@ -36,8 +36,8 @@ PUT _ml/anomaly_detectors/example1
3636 "analysis_config": {
3737 "detectors": [{
3838 "function" : "lat_long",
39- "field_name" : "transactionCoordinates ",
40- "by_field_name" : "creditCardNumber "
39+ "field_name" : "transaction_coordinates ",
40+ "by_field_name" : "credit_card_number "
4141 }]
4242 },
4343 "data_description": {
@@ -50,22 +50,23 @@ PUT _ml/anomaly_detectors/example1
5050
5151If you use this `lat_long` function in a detector in your {anomaly-job}, it
5252detects anomalies where the geographic location of a credit card transaction is
53- unusual for a particular customer’s credit card. An anomaly might indicate fraud.
53+ unusual for a particular customer’s credit card. An anomaly might indicate
54+ fraud.
5455
55- IMPORTANT: The `field_name` that you supply must be a single string that contains
56- two comma-separated numbers of the form `latitude,longitude`, a `geo_point` field,
57- a `geo_shape` field that contains point values, or a `geo_centroid` aggregation.
58- The `latitude` and `longitude` must be in the range -180 to 180 and represent a
59- point on the surface of the Earth.
56+ IMPORTANT: The `field_name` that you supply must be a single string that
57+ contains two comma-separated numbers of the form `latitude,longitude`, a
58+ `geo_point` field, a `geo_shape` field that contains point values, or a
59+ `geo_centroid` aggregation. The `latitude` and `longitude` must be in the range
60+ -180 to 180 and represent a point on the surface of the Earth.
6061
6162For example, JSON data might contain the following transaction coordinates:
6263
6364[source,js]
6465--------------------------------------------------
6566{
6667 "time": 1460464275,
67- "transactionCoordinates ": "40.7,-74.0",
68- "creditCardNumber ": "1234123412341234"
68+ "transaction_coordinates ": "40.7,-74.0",
69+ "credit_card_number ": "1234123412341234"
6970}
7071--------------------------------------------------
7172// NOTCONSOLE
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