From ca9cd56b86c384b642149aa9a33393119135bdea Mon Sep 17 00:00:00 2001 From: Anna Nowak Date: Mon, 24 May 2021 20:57:41 +0200 Subject: [PATCH] checkpoint pc --- .gitignore | 3 + ...sport text classification-checkpoint.ipynb | 204 +++++++++++++++++ sport text classification.ipynb | 213 ++++++++++++++++++ 3 files changed, 420 insertions(+) create mode 100644 .gitignore create mode 100644 .ipynb_checkpoints/sport text classification-checkpoint.ipynb create mode 100644 sport text classification.ipynb diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..fed376b --- /dev/null +++ b/.gitignore @@ -0,0 +1,3 @@ +train/train.tsv +.ipynb_checkpoints* +word2vec.model diff --git a/.ipynb_checkpoints/sport text classification-checkpoint.ipynb b/.ipynb_checkpoints/sport text classification-checkpoint.ipynb new file mode 100644 index 0000000..ba71208 --- /dev/null +++ b/.ipynb_checkpoints/sport text classification-checkpoint.ipynb @@ -0,0 +1,204 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Requirement already satisfied: gensim in c:\\users\\annad\\anaconda3\\lib\\site-packages (3.8.3)\n", + "Requirement already satisfied: smart-open>=1.8.1 in c:\\users\\annad\\anaconda3\\lib\\site-packages (from gensim) (5.0.0)\n", + "Requirement already satisfied: six>=1.5.0 in c:\\users\\annad\\anaconda3\\lib\\site-packages (from gensim) (1.15.0)\n", + "Requirement already satisfied: numpy>=1.11.3 in c:\\users\\annad\\anaconda3\\lib\\site-packages (from gensim) (1.19.2)\n", + "Requirement already satisfied: scipy>=0.18.1 in c:\\users\\annad\\anaconda3\\lib\\site-packages (from gensim) (1.5.2)\n", + "Requirement already satisfied: Cython==0.29.14 in c:\\users\\annad\\anaconda3\\lib\\site-packages (from gensim) (0.29.14)\n" + ] + } + ], + "source": [ + "!pip install gensim" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "import numpy as np\n", + "from gensim.test.utils import common_texts\n", + "from gensim.models import Word2Vec\n", + "import os.path" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "import gzip\n", + "import shutil\n", + "with gzip.open('train/train.tsv.gz', 'rb') as f_in:\n", + " with open('train/train.tsv', 'wb') as f_out:\n", + " shutil.copyfileobj(f_in, f_out)" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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01Mindaugas Budzinauskas wierzy w odbudowę formy...
11Przyjmujący reprezentacji Polski wrócił do PGE...
20FEN 9: Zapowiedź walki Róża Gumienna vs Katarz...
31Aleksander Filipiak: Czuję się dobrze w nowym ...
40Victoria Carl i Aleksiej Czerwotkin mistrzami ...
.........
981271Kamil Syprzak zaczyna kolekcjonować trofea. FC...
981281Holandia: dwa gole Piotra Parzyszka Piotr Parz...
981291Sparingowo: Korona gorsza od Stali. Lettieri s...
981301Vive - Wisła. Ośmiu debiutantów w tegorocznej ...
981311WTA Miami: Timea Bacsinszky pokonana, Swietłan...
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BallText
01Mindaugas Budzinauskas wierzy w odbudowę formy...
11Przyjmujący reprezentacji Polski wrócił do PGE...
20FEN 9: Zapowiedź walki Róża Gumienna vs Katarz...
31Aleksander Filipiak: Czuję się dobrze w nowym ...
40Victoria Carl i Aleksiej Czerwotkin mistrzami ...
.........
981271Kamil Syprzak zaczyna kolekcjonować trofea. FC...
981281Holandia: dwa gole Piotra Parzyszka Piotr Parz...
981291Sparingowo: Korona gorsza od Stali. Lettieri s...
981301Vive - Wisła. Ośmiu debiutantów w tegorocznej ...
981311WTA Miami: Timea Bacsinszky pokonana, Swietłan...
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98132 rows × 2 columns

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" + ], + "text/plain": [ + " Ball Text\n", + "0 1 Mindaugas Budzinauskas wierzy w odbudowę formy...\n", + "1 1 Przyjmujący reprezentacji Polski wrócił do PGE...\n", + "2 0 FEN 9: Zapowiedź walki Róża Gumienna vs Katarz...\n", + "3 1 Aleksander Filipiak: Czuję się dobrze w nowym ...\n", + "4 0 Victoria Carl i Aleksiej Czerwotkin mistrzami ...\n", + "... ... ...\n", + "98127 1 Kamil Syprzak zaczyna kolekcjonować trofea. FC...\n", + "98128 1 Holandia: dwa gole Piotra Parzyszka Piotr Parz...\n", + "98129 1 Sparingowo: Korona gorsza od Stali. Lettieri s...\n", + "98130 1 Vive - Wisła. Ośmiu debiutantów w tegorocznej ...\n", + "98131 1 WTA Miami: Timea Bacsinszky pokonana, Swietłan...\n", + "\n", + "[98132 rows x 2 columns]" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data = pd.read_csv('train/train.tsv', sep='\\t', names=[\"Ball\",\"Text\"])\n", + "data" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "model = None\n", + "sentences = [x.split() for x in data[\"Text\"]]\n", + "if not os.path.isfile('word2vec.model'):\n", + " model = Word2Vec(sentences=data[\"Text\"])\n", + " model.save(\"word2vec.model\")\n", + " model.train(sentences, total_examples=len(sentences), epochs=10)\n", + "else:\n", + " model = Word2Vec.load(\"word2vec.model\")" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "ename": "KeyError", + "evalue": "\"word 'Mindaugas' not in vocabulary\"", + "output_type": "error", + 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"\u001b[1;32m~\\anaconda3\\lib\\site-packages\\pandas\\core\\series.py\u001b[0m in \u001b[0;36mapply\u001b[1;34m(self, func, convert_dtype, args, **kwds)\u001b[0m\n\u001b[0;32m 4198\u001b[0m \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 4199\u001b[0m \u001b[0mvalues\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mastype\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mobject\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_values\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 4200\u001b[1;33m \u001b[0mmapped\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mlib\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmap_infer\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mvalues\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mf\u001b[0m\u001b[1;33m,\u001b[0m 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354\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 355\u001b[1;33m \u001b[1;32mreturn\u001b[0m \u001b[0mvstack\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_vector\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mentity\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mentity\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mentities\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 356\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 357\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0m__contains__\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mentity\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", + "\u001b[1;32m~\\anaconda3\\lib\\site-packages\\gensim\\models\\keyedvectors.py\u001b[0m in \u001b[0;36m\u001b[1;34m(.0)\u001b[0m\n\u001b[0;32m 353\u001b[0m \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_vector\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mentities\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 354\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 355\u001b[1;33m \u001b[1;32mreturn\u001b[0m \u001b[0mvstack\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_vector\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mentity\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mentity\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mentities\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 356\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 357\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0m__contains__\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m 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\u001b[0mwords_closer_than\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mw1\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mw2\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", + "\u001b[1;32m~\\anaconda3\\lib\\site-packages\\gensim\\models\\keyedvectors.py\u001b[0m in \u001b[0;36mword_vec\u001b[1;34m(self, word, use_norm)\u001b[0m\n\u001b[0;32m 466\u001b[0m \u001b[1;32mreturn\u001b[0m \u001b[0mresult\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 467\u001b[0m \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 468\u001b[1;33m \u001b[1;32mraise\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"word '%s' not in vocabulary\"\u001b[0m \u001b[1;33m%\u001b[0m \u001b[0mword\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 469\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 470\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mget_vector\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mword\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", + "\u001b[1;31mKeyError\u001b[0m: \"word 'Mindaugas' not in vocabulary\"" + ] + } + ], + "source": [ + "prepared_training_data['Text'] = prepared_training_data['Text'].apply(lambda x: model.wv[x.split()])" + ] + } + ], + "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": "3.8.5" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +}