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ver 2 10000 train

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Łukasz Jędyk 2021-05-12 21:22:41 +02:00
parent a2d5d926d0
commit 9dfe8fe3b5
3 changed files with 29 additions and 22 deletions
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20
dev-0/out.tsv
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@ -2399,7 +2399,7 @@
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8
main.py
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@ -1,3 +1,4 @@
import csv
import pandas as pd
from sklearn.linear_model import LinearRegression
from sklearn.pipeline import make_pipeline
@ -6,8 +7,8 @@ from sklearn.feature_extraction.text import TfidfVectorizer
col_names = ['start_date', 'end_date', 'title', 'source', 'content']
train_set = pd.read_table('train/train.tsv.xz', error_bad_lines=False, header=None, names=col_names)
dev_set = pd.read_table('dev-0/in.tsv', error_bad_lines=False, header=None, names=col_names[4:])
test_set = pd.read_table('test-A/in.tsv', error_bad_lines=False, header=None, names=col_names[4:])
dev_set = pd.read_table('dev-0/in.tsv', error_bad_lines=False, header=None, names=col_names[4:], quoting=csv.QUOTE_NONE,)
test_set = pd.read_table('test-A/in.tsv', error_bad_lines=False, header=None, names=col_names[4:], quoting=csv.QUOTE_NONE,)
train_set = train_set.head(10000)
@ -17,6 +18,9 @@ y_train = (train_set['start_date'] + train_set['end_date']) / 2
X_dev = dev_set['content']
X_test = test_set['content']
print(dev_set)
print(test_set)
print('Trenowanie modelu...')
model = make_pipeline(TfidfVectorizer(), LinearRegression())
model.fit(X_train, y_train)

23
test-A/out.tsv
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@ -206,7 +206,7 @@
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