Data Scaling (Z-Score, MinMax, Robust)

Scales features to improve model performance. Z-score for normal distributions, MinMax for bounded ranges (0-1), Robust for data with outliers. Essential preprocessing for distance-based algorithms. [Tier: ENTERPRISE, Credits: 10]

POST /quantlib/ml/preprocessing/scale

Data Scaling (Z-Score, MinMax, Robust)

cURL

curl --request POST \
  --url https://api.fincept.in/quantlib/ml/preprocessing/scale \
  --header 'Content-Type: application/json' \
  --header 'X-API-Key: <api-key>' \
  --data '
{
  "X": [
    [
      100,
      0.5
    ],
    [
      200,
      1.3
    ],
    [
      150,
      0.9
    ]
  ],
  "method": "zscore"
}
'

200

{
  "success": true,
  "data": {
    "scaled": [
      [
        -1.22,
        -1
      ],
      [
        1.22,
        1
      ],
      [
        0,
        0
      ]
    ],
    "method": "zscore"
  }
}

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 to scale

Example:

[[100, 0.5], [200, 1.3], [150, 0.9]]

method · enum<string> · default: zscore

Scaling method

Available options: zscore, minmax, robust

Example:

"zscore"

Response

200

application/json

Scaled data

success · boolean

Example:

true

data · object

Show child attributes