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finally... after platform change solution works

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szypol 2021-07-09 00:35:30 +02:00
parent e4adfb04dc
commit 148368be03
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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "f7e1ae0d",
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"import csv\n",
"from sklearn.feature_extraction.text import TfidfVectorizer\n",
"from sklearn.cluster import KMeans"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "7582a8dd",
"metadata": {},
"outputs": [],
"source": [
"#dev0\n",
"dev0_data = pd.read_csv('dev-0/in.tsv', header=None, quoting=csv.QUOTE_NONE, sep='\\t')\n",
"\n",
"dev0_y = KMeans(n_clusters=50).fit_predict(TfidfVectorizer().fit_transform(dev0_data[0].values))\n",
"\n",
"#zapis wyników\n",
"dev0_y.tofile('dev-0/out.tsv', sep='\\n')"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "d3c75abc",
"metadata": {},
"outputs": [],
"source": [
"#TestA\n",
"testA_data = pd.read_csv('test-A/in.tsv', header=None, quoting=csv.QUOTE_NONE, sep='\\t')\n",
"\n",
"testA_y = KMeans(n_clusters=50).fit_predict(TfidfVectorizer().fit_transform(testA_data[0].values))\n",
"\n",
"#zapis wyników\n",
"testA_y.tofile('test-A/out.tsv', sep='\\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": "3.8.8"
}
},
"nbformat": 4,
"nbformat_minor": 5
}

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#!/usr/bin/env python
# coding: utf-8
# In[1]:
import pandas as pd
import csv
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.cluster import KMeans
# In[2]:
#dev0
dev0_data = pd.read_csv('dev-0/in.tsv', header=None, quoting=csv.QUOTE_NONE, sep='\t')
dev0_y = KMeans(n_clusters=50).fit_predict(TfidfVectorizer().fit_transform(dev0_data[0].values))
#zapis wyników
dev0_y.tofile('dev-0/out.tsv', sep='\n')
# In[3]:
#TestA
testA_data = pd.read_csv('test-A/in.tsv', header=None, quoting=csv.QUOTE_NONE, sep='\t')
testA_y = KMeans(n_clusters=50).fit_predict(TfidfVectorizer().fit_transform(testA_data[0].values))
#zapis wyników
testA_y.tofile('test-A/out.tsv', sep='\n')

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