initial commit

GradientBoosting.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:034fc8eb71aec73ccdc3aef0ddd2632a38565fa7d42d014bc9605e41b22a6a81
+size 117183

app.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "6e9a9546",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Running on local URL:  http://127.0.0.1:7863\n",
+      "\n",
+      "To create a public link, set `share=True` in `launch()`.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div><iframe src=\"http://127.0.0.1:7863/\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": []
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import pickle\n",
+    "import pandas as pd\n",
+    "import gradio as gr\n",
+    "import warnings\n",
+    "warnings.filterwarnings('ignore')\n",
+    "\n",
+    "# Load the trained model\n",
+    "model = pickle.load(open('GradientBoosting.pkl', 'rb'))\n",
+    "\n",
+    "def word_happiness(Standard_Error, Economy_GDP_per_Capita, Family, Freedom, Trust_Government_Corruption, Generosity, Dystopia_Residual):\n",
+    "    # Prepare the input data as a DataFrame\n",
+    "    data = pd.DataFrame({\n",
+    "        'Standard_Error': [Standard_Error],\n",
+    "        'Economy_GDP_per_Capita': [Economy_GDP_per_Capita],\n",
+    "        'Family': [Family],\n",
+    "        'Freedom': [Freedom],\n",
+    "        'Trust_Government_Corruption': [Trust_Government_Corruption],\n",
+    "        'Generosity': [Generosity],\n",
+    "        'Dystopia_Residual': [Dystopia_Residual]\n",
+    "    })\n",
+    "\n",
+    "    # Perform the prediction\n",
+    "    prediction = model.predict(data)\n",
+    "    return prediction[0]\n",
+    "\n",
+    "# Create the input components\n",
+    "input_components = [\n",
+    "    gr.inputs.Number(label=\"Standard Error\"),\n",
+    "    gr.inputs.Number(label=\"Economy GDP per Capita\"),\n",
+    "    gr.inputs.Number(label=\"Family\"),\n",
+    "    gr.inputs.Number(label=\"Freedom\"),\n",
+    "    gr.inputs.Number(label=\"Trust Government Corruption\"),\n",
+    "    gr.inputs.Number(label=\"Generosity\"),\n",
+    "    gr.inputs.Number(label=\"Dystopia Residual\")\n",
+    "]\n",
+    "\n",
+    "# Create the interface\n",
+    "interface = gr.Interface(\n",
+    "    fn=word_happiness,\n",
+    "    inputs=input_components,\n",
+    "    outputs=\"number\",\n",
+    "    title=\"Word Happiness Report Project\",\n",
+    "    description=\"Word Happiness Report Project.\"\n",
+    ")\n",
+    "\n",
+    "# Launch the interface\n",
+    "interface.launch()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "46b8306d",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "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": "3.9.12"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

requirements.txt

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+scikit-learn == 1.0.2