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Sebastian 2022-05-18 00:59:01 +02:00
parent 3ade31cf7d
commit 75174effea
3 changed files with 91 additions and 65 deletions
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67
.ipynb_checkpoints/run-checkpoint.ipynb
View File

@ -44,7 +44,7 @@
"source": [
"train = pd.read_csv('train/train.tsv', header=None, sep='\\t', error_bad_lines=False)\n",
"print(len(train))\n",
"train = train.head(10000)"
"train = train[:10000]"
]
},
{
@ -60,7 +60,7 @@
},
{
"cell_type": "code",
"execution_count": 4,
"execution_count": null,
"id": "dd454ce5-a06e-4fbd-a546-83fb94ad0390",
"metadata": {},
"outputs": [],
@ -74,7 +74,7 @@
},
{
"cell_type": "code",
"execution_count": 5,
"execution_count": 4,
"id": "0a1cce75-86a1-4f76-9416-e876e01699e3",
"metadata": {},
"outputs": [
@ -85,7 +85,7 @@
" ('linearregression', LinearRegression())])"
]
},
"execution_count": 5,
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
@ -97,7 +97,7 @@
},
{
"cell_type": "code",
"execution_count": 6,
"execution_count": null,
"id": "cc1270d5-29dc-4f03-82c1-dc03f3e4fa00",
"metadata": {},
"outputs": [],
@ -114,25 +114,47 @@
},
{
"cell_type": "code",
"execution_count": 7,
"execution_count": 5,
"id": "2fd18dfa-0dba-460b-a56d-21793baa7124",
"metadata": {},
"outputs": [],
"source": [
"def readFile(filename):\n",
" result = []\n",
" with open(filename, 'r', encoding=\"utf-8\") as file:\n",
" for line in file:\n",
" text = line.split(\"\\t\")[0].strip()\n",
" result.append(text)\n",
" return result"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "ce918d1f-2b8d-432c-be19-3a4966062d35",
"metadata": {},
"outputs": [],
"source": [
"x_dev = readFile('dev-0/in.tsv')\n",
"dev_predicted = model.predict(x_dev)\n",
"with open('dev-0/out.tsv', 'wt') as f:\n",
" for i in dev_predicted:\n",
" f.write(str(i)+'\\n')"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "223de995-5e91-4254-9214-4fc871c985e9",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"4086.3369441409172\n"
]
}
],
"outputs": [],
"source": [
"print(mean_squared_error(dev_out, dev_expected))"
]
},
{
"cell_type": "code",
"execution_count": 8,
"execution_count": 7,
"id": "3bc8418b-64f1-4163-a0ec-8e3293032341",
"metadata": {},
"outputs": [],
@ -152,19 +174,10 @@
},
{
"cell_type": "code",
"execution_count": 9,
"execution_count": null,
"id": "a18aea56-7fa1-40bd-8aa3-bbaf9d66d6b7",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"[NbConvertApp] Converting notebook run.ipynb to script\n",
"[NbConvertApp] Writing 1607 bytes to run.py\n"
]
}
],
"outputs": [],
"source": [
"!jupyter nbconvert --to script run.ipynb"
]

22
dev-0/out.tsv
View File

@ -2399,7 +2399,7 @@
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1808.2574401126217
@ -4770,7 +4770,7 @@
1869.069137844269
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1945.2161014273179
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1897.6394497272986
1902.242330620895
1916.8264849806906
1951.121108306926
@ -6336,7 +6336,8 @@
1974.1360045857598
1851.0358973964571
1837.1785138354128
1920.829667692275
1906.347666040038
1941.0011085451317
1862.9050427724196
1935.236110299957
1838.7213811070148
@ -11780,7 +11781,7 @@
1971.0497213398978
1965.6443681542146
1893.8995265026135
1843.5424552030524
1843.369474418135
1798.0577429814193
1874.3107569198335
1933.8681512671249
@ -11868,7 +11869,7 @@
1933.2279243717342
1948.4195648206846
1891.657975325964
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1882.2766120936951
1898.8213099251864
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@ -13607,7 +13608,8 @@
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1831.7070096790642
1830.5322687720245
1859.0850481271784
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1821.4668780375355
1912.9269712307623
1984.9697444709716
@ -14150,7 +14152,7 @@
1958.8896600656121
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@ -17368,7 +17370,7 @@
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1970.6462880262288
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@ -19795,7 +19797,7 @@
1917.2137752775773
1850.5061783561657
1911.974999970517
1837.7085426751216
1837.5419178319084
1970.1179076824587
1955.9219153909546
1941.3082376506911
@ -19996,5 +19998,3 @@
1998.999096707664
1906.1529351577549
1982.0734958856071
1972.9762321594746
1976.0692324960928

1 1839.7731901418288
2399 1882.922191542162
2400 2006.349306172171
2401 1901.7102363782105
2402 1845.5158880914453 1845.9729647936565
2403 1907.098520568831
2404 1918.9780895683843
2405 1808.2574401126217
4770 1869.069137844269
4771 1906.274740877195
4772 1945.2161014273179
4773 1897.764739918972 1897.6394497272986
4774 1902.242330620895
4775 1916.8264849806906
4776 1951.121108306926
6336 1974.1360045857598
6337 1851.0358973964571
6338 1837.1785138354128
6339 1920.829667692275 1906.347666040038
6340 1941.0011085451317
6341 1862.9050427724196
6342 1935.236110299957
6343 1838.7213811070148
11781 1971.0497213398978
11782 1965.6443681542146
11783 1893.8995265026135
11784 1843.5424552030524 1843.369474418135
11785 1798.0577429814193
11786 1874.3107569198335
11787 1933.8681512671249
11869 1933.2279243717342
11870 1948.4195648206846
11871 1891.657975325964
11872 1881.6018296953764 1882.2766120936951
11873 1898.8213099251864
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13609 1831.7070096790642
13610 1830.5322687720245
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13612 1886.4495007457836
13613 1821.4668780375355
13614 1912.9269712307623
13615 1984.9697444709716
14152 1958.8896600656121
14153 1917.5200385639437
14154 1904.7837664328952
14155 1871.5148054544618 1871.1791610952482
14156 1900.9087322958958
14157 1871.5459519347532
14158 1965.7232636496624
17370 1863.8359491028696
17371 1980.291829241186
17372 1819.6648275839043
17373 1856.061958173075 1855.3731584258308
17374 1921.5280792457972
17375 1970.6462880262288
17376 1902.5179505003136
19797 1917.2137752775773
19798 1850.5061783561657
19799 1911.974999970517
19800 1837.7085426751216 1837.5419178319084
19801 1970.1179076824587
19802 1955.9219153909546
19803 1941.3082376506911
19998 1998.999096707664
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20000 1982.0734958856071
1972.9762321594746
1976.0692324960928

67
run.ipynb
View File

@ -44,7 +44,7 @@
"source": [
"train = pd.read_csv('train/train.tsv', header=None, sep='\\t', error_bad_lines=False)\n",
"print(len(train))\n",
"train = train.head(10000)"
"train = train[:10000]"
]
},
{
@ -60,7 +60,7 @@
},
{
"cell_type": "code",
"execution_count": 4,
"execution_count": null,
"id": "dd454ce5-a06e-4fbd-a546-83fb94ad0390",
"metadata": {},
"outputs": [],
@ -74,7 +74,7 @@
},
{
"cell_type": "code",
"execution_count": 5,
"execution_count": 4,
"id": "0a1cce75-86a1-4f76-9416-e876e01699e3",
"metadata": {},
"outputs": [
@ -85,7 +85,7 @@
" ('linearregression', LinearRegression())])"
]
},
"execution_count": 5,
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
@ -97,7 +97,7 @@
},
{
"cell_type": "code",
"execution_count": 6,
"execution_count": null,
"id": "cc1270d5-29dc-4f03-82c1-dc03f3e4fa00",
"metadata": {},
"outputs": [],
@ -114,25 +114,47 @@
},
{
"cell_type": "code",
"execution_count": 7,
"execution_count": 5,
"id": "2fd18dfa-0dba-460b-a56d-21793baa7124",
"metadata": {},
"outputs": [],
"source": [
"def readFile(filename):\n",
" result = []\n",
" with open(filename, 'r', encoding=\"utf-8\") as file:\n",
" for line in file:\n",
" text = line.split(\"\\t\")[0].strip()\n",
" result.append(text)\n",
" return result"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "ce918d1f-2b8d-432c-be19-3a4966062d35",
"metadata": {},
"outputs": [],
"source": [
"x_dev = readFile('dev-0/in.tsv')\n",
"dev_predicted = model.predict(x_dev)\n",
"with open('dev-0/out.tsv', 'wt') as f:\n",
" for i in dev_predicted:\n",
" f.write(str(i)+'\\n')"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "223de995-5e91-4254-9214-4fc871c985e9",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"4086.3369441409172\n"
]
}
],
"outputs": [],
"source": [
"print(mean_squared_error(dev_out, dev_expected))"
]
},
{
"cell_type": "code",
"execution_count": 8,
"execution_count": 7,
"id": "3bc8418b-64f1-4163-a0ec-8e3293032341",
"metadata": {},
"outputs": [],
@ -152,19 +174,10 @@
},
{
"cell_type": "code",
"execution_count": 9,
"execution_count": null,
"id": "a18aea56-7fa1-40bd-8aa3-bbaf9d66d6b7",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"[NbConvertApp] Converting notebook run.ipynb to script\n",
"[NbConvertApp] Writing 1607 bytes to run.py\n"
]
}
],
"outputs": [],
"source": [
"!jupyter nbconvert --to script run.ipynb"
]