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1 | 1 | {
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2 | 2 | "cells": [
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| 3 | + { |
| 4 | + "cell_type": "markdown", |
| 5 | + "id": "ce92c898", |
| 6 | + "metadata": {}, |
| 7 | + "source": [ |
| 8 | + "<td>\n", |
| 9 | + " <a target=\"_blank\" href=\"https://labelbox.com\" ><img src=\"https://labelbox.com/blog/content/images/2021/02/logo-v4.svg\" width=256/></a>\n", |
| 10 | + "</td>" |
| 11 | + ] |
| 12 | + }, |
| 13 | + { |
| 14 | + "cell_type": "markdown", |
| 15 | + "id": "5d6ab814", |
| 16 | + "metadata": {}, |
| 17 | + "source": [ |
| 18 | + "<td>\n", |
| 19 | + "<a href=\"https://colab.research.google.com/github/Labelbox/labelbox-python/blob/develop/examples/extras/classification-confusion-matrix\" target=\"_blank\"><img\n", |
| 20 | + "src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"></a>\n", |
| 21 | + "</td>\n", |
| 22 | + "\n", |
| 23 | + "<td>\n", |
| 24 | + "<a href=\"https://github.com/Labelbox/labelbox-python/tree/develop/examples/extras/classification-confusion-matrix.ipynb\" target=\"_blank\"><img\n", |
| 25 | + "src=\"https://img.shields.io/badge/GitHub-100000?logo=github&logoColor=white\" alt=\"GitHub\"></a>\n", |
| 26 | + "</td>" |
| 27 | + ] |
| 28 | + }, |
3 | 29 | {
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4 | 30 | "cell_type": "markdown",
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5 | 31 | "id": "47170397",
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9 | 35 | "\n",
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10 | 36 | "This notebook plots a confusion matrix for a multi-class, single label classification.\n",
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11 | 37 | "\n",
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12 |
| - "It assumes that your project has a number of labels from multiple labelers, where the Annotation Type is Radio." |
| 38 | + "It assumes that your project has a number of labels from multiple labelers, where the Annotation Type is Radio.\n", |
| 39 | + "\n", |
| 40 | + "## Installs" |
| 41 | + ] |
| 42 | + }, |
| 43 | + { |
| 44 | + "cell_type": "code", |
| 45 | + "execution_count": null, |
| 46 | + "id": "bf8c817c", |
| 47 | + "metadata": {}, |
| 48 | + "outputs": [], |
| 49 | + "source": [ |
| 50 | + "!pip install -q 'labelbox[data]'" |
| 51 | + ] |
| 52 | + }, |
| 53 | + { |
| 54 | + "cell_type": "markdown", |
| 55 | + "id": "b338a06e", |
| 56 | + "metadata": { |
| 57 | + "ExecuteTime": { |
| 58 | + "end_time": "2022-02-25T17:21:41.598592Z", |
| 59 | + "start_time": "2022-02-25T17:21:41.595703Z" |
| 60 | + } |
| 61 | + }, |
| 62 | + "source": [ |
| 63 | + "## Imports" |
13 | 64 | ]
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14 | 65 | },
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15 | 66 | {
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130 | 181 | "dataset = lb.get_dataset('xxx')"
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131 | 182 | ]
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132 | 183 | },
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| 184 | + { |
| 185 | + "cell_type": "markdown", |
| 186 | + "id": "88c31726", |
| 187 | + "metadata": {}, |
| 188 | + "source": [ |
| 189 | + "## Labeler Selection" |
| 190 | + ] |
| 191 | + }, |
133 | 192 | {
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134 | 193 | "cell_type": "code",
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135 | 194 | "execution_count": 13,
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180 | 239 | "widgets.VBox(items)"
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181 | 240 | ]
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182 | 241 | },
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| 242 | + { |
| 243 | + "cell_type": "markdown", |
| 244 | + "id": "95a7eed3", |
| 245 | + "metadata": {}, |
| 246 | + "source": [ |
| 247 | + "## Confusion Matrix" |
| 248 | + ] |
| 249 | + }, |
183 | 250 | {
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184 | 251 | "cell_type": "code",
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185 | 252 | "execution_count": 16,
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