curl --request POST \
  --url https://api.fincept.in/quantlib/ml/regression/fit \
  --header 'Content-Type: application/json' \
  --header 'X-API-Key: <api-key>' \
  --data '
{
  "X": [
    [
      1.2,
      0.5
    ],
    [
      2.1,
      1.3
    ],
    [
      0.8,
      0.9
    ]
  ],
  "y": [
    150000,
    235000,
    185000
  ],
  "method": "lasso",
  "alpha": 0.1,
  "l1_ratio": 0.5,
  "predict_X": [
    [
      1.5,
      0.7
    ]
  ]
}
'

import requests

url = "https://api.fincept.in/quantlib/ml/regression/fit"

payload = {
    "X": [[1.2, 0.5], [2.1, 1.3], [0.8, 0.9]],
    "y": [150000, 235000, 185000],
    "method": "lasso",
    "alpha": 0.1,
    "l1_ratio": 0.5,
    "predict_X": [[1.5, 0.7]]
}
headers = {
    "X-API-Key": "<api-key>",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.text)

const options = {
  method: 'POST',
  headers: {'X-API-Key': '<api-key>', 'Content-Type': 'application/json'},
  body: JSON.stringify({
    X: [[1.2, 0.5], [2.1, 1.3], [0.8, 0.9]],
    y: [150000, 235000, 185000],
    method: 'lasso',
    alpha: 0.1,
    l1_ratio: 0.5,
    predict_X: [[1.5, 0.7]]
  })
};

fetch('https://api.fincept.in/quantlib/ml/regression/fit', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://api.fincept.in/quantlib/ml/regression/fit",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
  CURLOPT_POSTFIELDS => json_encode([
    'X' => [
        [
                1.2,
                0.5
        ],
        [
                2.1,
                1.3
        ],
        [
                0.8,
                0.9
        ]
    ],
    'y' => [
        150000,
        235000,
        185000
    ],
    'method' => 'lasso',
    'alpha' => 0.1,
    'l1_ratio' => 0.5,
    'predict_X' => [
        [
                1.5,
                0.7
        ]
    ]
  ]),
  CURLOPT_HTTPHEADER => [
    "Content-Type: application/json",
    "X-API-Key: <api-key>"
  ],
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

package main

import (
	"fmt"
	"strings"
	"net/http"
	"io"
)

func main() {

	url := "https://api.fincept.in/quantlib/ml/regression/fit"

	payload := strings.NewReader("{\n  \"X\": [\n    [\n      1.2,\n      0.5\n    ],\n    [\n      2.1,\n      1.3\n    ],\n    [\n      0.8,\n      0.9\n    ]\n  ],\n  \"y\": [\n    150000,\n    235000,\n    185000\n  ],\n  \"method\": \"lasso\",\n  \"alpha\": 0.1,\n  \"l1_ratio\": 0.5,\n  \"predict_X\": [\n    [\n      1.5,\n      0.7\n    ]\n  ]\n}")

	req, _ := http.NewRequest("POST", url, payload)

	req.Header.Add("X-API-Key", "<api-key>")
	req.Header.Add("Content-Type", "application/json")

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

HttpResponse<String> response = Unirest.post("https://api.fincept.in/quantlib/ml/regression/fit")
  .header("X-API-Key", "<api-key>")
  .header("Content-Type", "application/json")
  .body("{\n  \"X\": [\n    [\n      1.2,\n      0.5\n    ],\n    [\n      2.1,\n      1.3\n    ],\n    [\n      0.8,\n      0.9\n    ]\n  ],\n  \"y\": [\n    150000,\n    235000,\n    185000\n  ],\n  \"method\": \"lasso\",\n  \"alpha\": 0.1,\n  \"l1_ratio\": 0.5,\n  \"predict_X\": [\n    [\n      1.5,\n      0.7\n    ]\n  ]\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.fincept.in/quantlib/ml/regression/fit")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["X-API-Key"] = '<api-key>'
request["Content-Type"] = 'application/json'
request.body = "{\n  \"X\": [\n    [\n      1.2,\n      0.5\n    ],\n    [\n      2.1,\n      1.3\n    ],\n    [\n      0.8,\n      0.9\n    ]\n  ],\n  \"y\": [\n    150000,\n    235000,\n    185000\n  ],\n  \"method\": \"lasso\",\n  \"alpha\": 0.1,\n  \"l1_ratio\": 0.5,\n  \"predict_X\": [\n    [\n      1.5,\n      0.7\n    ]\n  ]\n}"

response = http.request(request)
puts response.read_body

{
  "success": true,
  "data": {
    "coefficients": [
      85000,
      120000
    ],
    "intercept": 50000,
    "r_squared": 0.847,
    "predictions": [
      197500
    ]
  }
}

{
  "detail": "Invalid API key"
}

{
  "detail": "Insufficient credits. This endpoint requires 5 credits."
}

{
  "detail": [
    {
      "loc": [
        "<string>"
      ],
      "msg": "<string>",
      "type": "<string>"
    }
  ]
}