.idea/.gitignore

@@ -1,8 +0,0 @@
-# Default ignored files
-/shelf/
-/workspace.xml
-# Editor-based HTTP Client requests
-/httpRequests/
-# Datasource local storage ignored files
-/dataSources/
-/dataSources.local.xml

.idea/inspectionProfiles/profiles_settings.xml

@@ -1,6 +0,0 @@
-<component name="InspectionProjectProfileManager">
-  <settings>
-    <option name="USE_PROJECT_PROFILE" value="false" />
-    <version value="1.0" />
-  </settings>
-</component>

.idea/misc.xml

@@ -1,4 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<project version="4">
-  <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.10" project-jdk-type="Python SDK" />
-</project>

.idea/modules.xml

@@ -1,8 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<project version="4">
-  <component name="ProjectModuleManager">
-    <modules>
-      <module fileurl="file://$PROJECT_DIR$/.idea/retroc2.iml" filepath="$PROJECT_DIR$/.idea/retroc2.iml" />
-    </modules>
-  </component>
-</project>

.idea/retroc2.iml

@@ -1,8 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<module type="PYTHON_MODULE" version="4">
-  <component name="NewModuleRootManager">
-    <content url="file://$MODULE_DIR$" />
-    <orderEntry type="inheritedJdk" />
-    <orderEntry type="sourceFolder" forTests="false" />
-  </component>
-</module>

.idea/vcs.xml

@@ -1,6 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<project version="4">
-  <component name="VcsDirectoryMappings">
-    <mapping directory="$PROJECT_DIR$" vcs="Git" />
-  </component>
-</project>

run.py

@@ -1,51 +0,0 @@
-import lzma
-import math
-from sklearn.feature_extraction.text import TfidfVectorizer
-from sklearn.linear_model import LinearRegression
-from sklearn.pipeline import make_pipeline
-from sklearn.metrics import mean_squared_error
-import pandas as pd
-
-X_train = []
-Y_train = []
-
-stop = 0
-
-with lzma.open('train/train.tsv.xz', 'rt', encoding="utf-8") as f:
-    data = pd.read_csv(f, sep='\t', names=['Begin', 'End', 'Text'])
-
-
-data = data[['Text', 'End']]
-data = data[0:50000]
-
-X = data['Text']
-y = data['End']
-
-model = make_pipeline(TfidfVectorizer(), LinearRegression())
-model.fit(X, y)
-
-
-def readFile(filename):
-    X_dev = []
-    with open(filename, 'r', encoding="utf-8") as dev_in:
-        for line in dev_in:
-            text = line.split("\t")[0].strip()
-            X_dev.append(text)
-    return X_dev
-
-def writePred(filename, predictions):
-    with open(filename, "w") as out_file:
-        for pred in predictions:
-            out_file.write(str(pred) + "\n")
-
-x = readFile('dev-0/in.tsv')
-pred = model.predict(x)
-writePred('dev-0/out.tsv',pred)
-
-x = readFile('dev-1/in.tsv')
-pred = model.predict(x)
-writePred('dev-1/out.tsv',pred)
-
-x = readFile('test-A/in.tsv')
-pred = model.predict(x)
-writePred('test-A/out.tsv',pred)