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fit linear regression python scikit

AartvB answered on September 13, 2024 Popularity 3/10 Helpfulness 1/10

answer fit linear regression python scikit

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fit linear regression python scikit

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import numpy as np
>>> from sklearn.linear_model import LinearRegression
>>> X = np.array([[1, 1], [1, 2], [2, 2], [2, 3]])
>>> # y = 1 * x_0 + 2 * x_1 + 3
>>> y = np.dot(X, np.array([1, 2])) + 3
>>> reg = LinearRegression().fit(X, y)
>>> reg.score(X, y)
1.0
>>> reg.coef_
array([1., 2.])
>>> reg.intercept_
np.float64(3.0...)
>>> reg.predict(np.array([[3, 5]]))
array([16.])

Popularity 3/10 Helpfulness 1/10 Language python

Source: scikit-learn.org

Tags: linear-regression python

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Contributed on Sep 13 2024

AartvB

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variable "containers" {
  type = list(object({
    container_name = string
    image_service  = string
    image_version  = string
    port           = map(any)
  }))
  default = [
    {
      container_name = "tf-nginx"
      image_service  = "nginx"
      image_version  = "nginx:alpine"
      port = {
        service = 80
      }
    },
    {
      container_name = "tf-rabbitmq"
      image_service  = "rabbitmq"
      image_version  = "3-management-alpine"
      port = {
        service   = 5672
        dashboard = 15672
      }
    }
  ]
}

resource "docker_image" "nginx" { # docker pull nginx:stable
  for_each = tomap({
    for container in var.containers : "${container.image_service}:${container.image_version}" => container
  })

  name = each.value.image_version
}

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Source: Grepper

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Contributed on Sep 13 2024

Restu Wahyu Saputra

0 Answers Avg Quality 2/10

fit linear regression python scikit

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fit linear regression python scikit

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