ML_simplified.ipynb

ml_simplified.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "authorship_tag": "ABX9TyMBiN2CXc9kZvRondGY1drE",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/gist/aicentral/24d6e41e82c6af87ffb7c8c2f640e86f/ml_simplified.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "vtWXmu9y3FJW",
        "outputId": "2d54c26e-c0c2-41c5-b37b-a544e897e5c0"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "The variance of each of the three features is:\n",
            "[2.31875e+01 2.18750e-02 4.25000e+00]\n",
            "The feature with the least variance is:\n",
            "Width\n"
          ]
        }
      ],
      "source": [
        "'''\n",
        "Fining the feature witht he least variance.\n",
        "'''\n",
        "import numpy as np\n",
        "feature_names = ['Length', 'Width', 'Hieght']\n",
        "measurements = [[25, 5, 10],\n",
        "                [24, 4.9, 9],\n",
        "                [35, 4.8, 13],\n",
        "                [33, 5.2, 14]]\n",
        "\n",
        "feature_variance = np.var(measurements,axis=0)\n",
        "print('The variance of each of the three features is:')\n",
        "print(feature_variance)\n",
        "# Now, locate the feature with the least variance\n",
        "least_var_feature_idx = np.argmin(feature_variance)\n",
        "# Find the name of that feature\n",
        "least_var_feature_name = feature_names[least_var_feature_idx]\n",
        "print('The feature with the least variance is:')\n",
        "print(least_var_feature_name)"
      ]
    }
  ]
}