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Adrian Charkiewicz 2022-04-13 16:58:26 +02:00
parent b775a221e6
commit e310d99b89
3 changed files with 257 additions and 0 deletions
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6
dev-0/.ipynb_checkpoints/model-checkpoint.ipynb Normal file
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{
"cells": [],
"metadata": {},
"nbformat": 4,
"nbformat_minor": 5
}

3
dev-0/.jovianrc Normal file
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{
"notebooks": {}
}

248
dev-0/model.ipynb Normal file
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{
"cells": [
{
"cell_type": "code",
"execution_count": 90,
"id": "5b55a105",
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"import csv"
]
},
{
"cell_type": "code",
"execution_count": 91,
"id": "9364cf2c",
"metadata": {},
"outputs": [],
"source": [
"tsv_data = pd.read_csv('in.tsv', sep='\\t',header=None, quoting=csv.QUOTE_NONE)[0]"
]
},
{
"cell_type": "code",
"execution_count": 139,
"id": "9d3f7db9",
"metadata": {},
"outputs": [],
"source": [
"expected = pd.read_csv('expected.tsv', sep='\\t',header=None)[0]"
]
},
{
"cell_type": "code",
"execution_count": 94,
"id": "5062478d",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"137314\n",
"137314\n"
]
}
],
"source": [
"print(len(expected))\n",
"print(len(tsv_data))"
]
},
{
"cell_type": "code",
"execution_count": 158,
"id": "5eca7aab",
"metadata": {},
"outputs": [],
"source": [
"male={'silnik', 'windows', 'gb', 'mb', 'mecz', 'pc', 'opony', 'apple', 'iphone', 'zwiastuny', 'hd', 'ubuntu', 'system', 'serwer'}\n",
"female={'ciąża', 'miesiączki', 'ciasto', 'ciąże', 'zadowolona', 'antykoncepcyjne', 'ginekologia', 'tabletki', 'porodzie', 'mąż', 'krwawienie', 'ciasta'}\n",
"male = {x[:6].lower() for x in male}\n",
"female = {x[:6].lower() for x in female}"
]
},
{
"cell_type": "code",
"execution_count": 159,
"id": "0bdd1845",
"metadata": {},
"outputs": [],
"source": [
"trimmed_docs=[]\n",
"for document in tsv_data:\n",
" new_doc=[]\n",
" for word in str(document).lower().split():\n",
" new_doc.append(word[:6])\n",
" trimmed_docs.append(new_doc)"
]
},
{
"cell_type": "code",
"execution_count": 160,
"id": "b36bbd92",
"metadata": {},
"outputs": [],
"source": [
"male_or_female=[]\n",
"for doc in trimmed_docs:\n",
" male_or_female.append((len(male&set(doc)), len(female&set(doc))))"
]
},
{
"cell_type": "code",
"execution_count": 161,
"id": "ccbad95c",
"metadata": {},
"outputs": [],
"source": [
"answers=[]\n",
"for i in male_or_female:\n",
" if i[0]>i[1]:\n",
" answers.append(1)\n",
" else:\n",
" answers.append(0)"
]
},
{
"cell_type": "code",
"execution_count": 162,
"id": "02ee0acf",
"metadata": {},
"outputs": [],
"source": [
"result=[]\n",
"for i in range(len(answers)):\n",
" if answers[i]==expected[i]:\n",
" result.append(1)\n",
" else:\n",
" result.append(0)\n"
]
},
{
"cell_type": "code",
"execution_count": 163,
"id": "db803a58",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Predykcja modelu wynosi 51.007909%\n"
]
}
],
"source": [
"print(f'Predykcja modelu wynosi {sum(result)/len(result)*100:.6f}%')"
]
},
{
"cell_type": "code",
"execution_count": 164,
"id": "e1a15db7",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"['cierpi',\n",
" 'na',\n",
" 'strasz',\n",
" 'lagi',\n",
" '–',\n",
" 'kilkan',\n",
" 'sekund',\n",
" 'lub',\n",
" 'dłużej',\n",
" 'czarne',\n",
" 'ekranu',\n",
" 'przy',\n",
" 'próbie',\n",
" 'przełą',\n",
" 'się',\n",
" '/',\n",
" 'urucho',\n",
" 'prawie',\n",
" 'każdej',\n",
" 'aplika',\n",
" 'dodatk',\n",
" 'telefo',\n",
" 'mi',\n",
" 'się',\n",
" 'wyłącz',\n",
" 'czasem',\n",
" 'bez',\n",
" 'powodu',\n",
" '–',\n",
" 'sam',\n",
" 'z',\n",
" 'siebie',\n",
" 'albo',\n",
" 'reseto',\n",
" 'ostatn',\n",
" 'nawet',\n",
" 'przegl',\n",
" 'zaczęł',\n",
" 'się',\n",
" 'często',\n",
" 'zawies',\n",
" 'i',\n",
" 'androi',\n",
" 'propon',\n",
" 'wymusz',\n",
" 'zamkni',\n",
" 'do',\n",
" 'tego',\n",
" 'te',\n",
" 'proble',\n",
" 'z',\n",
" 'połącz',\n",
" 'do',\n",
" 'komput',\n",
" 'przez',\n",
" 'usb.']"
]
},
"execution_count": 164,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"trimmed_docs[0]"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "7403c1bb",
"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": "3.9.7"
}
},
"nbformat": 4,
"nbformat_minor": 5
}