final

linear.ipynb

@@ -0,0 +1,89 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from sklearn.feature_extraction.text import TfidfVectorizer\n",
+    "from sklearn.linear_model import LinearRegression\n",
+    "from stop_words import get_stop_words\n",
+    "import pandas as pd\n",
+    "import numpy as np"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "vectorizer = TfidfVectorizer(stop_words = get_stop_words('polish'))\n",
+    "linear = LinearRegression()\n",
+    "\n",
+    "train = pd.read_csv('train/train.tsv', sep = \"\\t\", names = ['start_date', 'end_date', 'title', 'sort_title', 'data'])\n",
+    "\n",
+    "mean = (train['start_date'] + train['end_date']) / 2\n",
+    "tv = vectorizer.fit_transform(train['data'])\n",
+    "linear.fit(tv, mean)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def getData(directory):\n",
+    "    with open(directory, encoding=\"utf-8\") as file:\n",
+    "          return file.readlines()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "tmp_dev = getData('dev-0/in.tsv')\n",
+    "dataFrame_dev = pd.DataFrame(data = tmp_dev)\n",
+    "evaluate_dev = linear.predict(vectorizer.transform(dataFrame_dev[0]))\n",
+    "np.savetxt('dev-0/out.tsv', evaluate, fmt='%f', delimiter='\\n')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "tmp_test = getData('test-A/in.tsv')\n",
+    "dataFrame_test = pd.DataFrame(data = tmp_test)\n",
+    "evaluate_test = linear.predict(vectorizer.transform(dataFrame_test[0]))\n",
+    "np.savetxt('test-A/out.tsv', evaluate, fmt='%f', delimiter='\\n')"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "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": "3.7.0"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}