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POST
/
quantlib
/
ml
/
preprocessing
/
outliers
Outlier Detection
curl --request POST \
  --url https://api.fincept.in/quantlib/ml/preprocessing/outliers \
  --header 'Content-Type: application/json' \
  --header 'X-API-Key: <api-key>' \
  --data '
{
  "X": [
    [
      1.2,
      0.5
    ],
    [
      1.3,
      0.6
    ],
    [
      1.1,
      0.5
    ],
    [
      10,
      10
    ]
  ],
  "method": "zscore",
  "threshold": 3
}
'
{
  "success": true,
  "data": {
    "outliers": [
      false,
      false,
      false,
      true
    ],
    "outlier_indices": [
      3
    ]
  }
}

Authorizations

​
X-API-Key
string
header
required

API key for authentication. Get your key at https://api.fincept.in/auth/register

Body

application/json
​
X
number[][]
required

Feature matrix

Example:
[
  [1.2, 0.5],
  [1.3, 0.6],
  [1.1, 0.5],
  [10, 10]
]
​
method
enum<string>
default:zscore

Outlier detection method

Available options:
zscore,
iqr,
mad
Example:

"zscore"

​
threshold
number
default:3

Threshold for outlier detection (e.g., 3.0 for 3-sigma)

Example:

3

Response

Outlier detection results

​
success
boolean
Example:

true

​
data
object