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(\"Linear Regression\", \"gray\", 101.56),\n", " (\"NLP + LR\", \"gray\", 76.81),\n", " (\"Random Forest\", \"gray\", 72.28),\n", " (\"XGBoost\", \"gray\", 68.23),\n", " (\"Human (Ed)\", \"black\", 87.62),\n", " (\"Neural Network\", \"orange\", 63.97),\n", " (\"GPT 4.1 Nano\", \"slateblue\", 62.51),\n", " (\"Grok 4.1 Fast\", \"slateblue\", 57.62),\n", " (\"Gemini 3 Pro\", \"slateblue\", 50.54),\n", " (\"Claude 4.5 Sonnet\", \"slateblue\", 47.10),\n", " (\"GPT 5.1\", \"slateblue\", 44.74),\n", " (\"GPT 4.1 Nano (Fine-tuned)\", \"skyblue\", 75.91),\n", " (\"Deep Neural Network\", \"orange\", 46.49),\n", " (\"Base Llama 3.2 4 bit\", \"darkred\", 110.72),\n", " (\"Fine-tuned Lite\", \"red\", 65.40),\n", " (\"Fine-tuned Full\", \"red\", 39.85),\n", " (\"GPT 5.1 RAG\", \"green\", 30.19),\n", " (\"Ensemble\", \"purple\", 29.9)\n", "]\n", "\n", "labels, colors, values = zip(*results)\n", "\n", "fig = go.Figure(go.Bar(x=labels, y=values, marker_color=colors))\n", "\n", "fig.update_layout(\n", " title=\"Prediction error from each model\",\n", " yaxis=dict(range=[0, max(values)], title=\"Error\"),\n", " xaxis=dict(tickangle=-45),\n", " width=1000,\n", " height=800\n", ")\n", "\n", "fig.show()" ] }, { "cell_type": "code", "execution_count": null, "id": "bfac7653", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "id": "de22d815", "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": ".venv", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.12.12" } }, "nbformat": 4, "nbformat_minor": 5 }