4.3.1 v8
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@ -4,3 +4,10 @@ RUN apt-get update && \
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apt-get install -y python3 python3-pip
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apt-get install -y python3 python3-pip
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RUN pip3 install pandas numpy
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RUN pip3 install pandas numpy
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WORKDIR /app
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COPY create-dataset.py /app
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COPY data/barcelona_weekends.csv /app
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CMD ["python3", "create-dataset.py"]
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@ -44,12 +44,7 @@ pipeline {
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dockerfile true
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dockerfile true
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}
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}
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steps {
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steps {
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sh 'python3 create-dataset.py'
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archiveArtifacts artifacts: 'barcelona_weekends.train.csv, barcelona_weekends.dev.csv, barcelona_weekends.test.csv', fingerprint: true
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}
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}
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stage('Archive') {
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steps {
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archiveArtifacts artifacts: 'data/barcelona_weekends.train.csv, data/barcelona_weekends.dev.csv, data/barcelona_weekends.test.csv', fingerprint: true
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}
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}
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}
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}
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}
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}
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@ -5,16 +5,16 @@ import numpy as np
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cutoff = 10
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cutoff = 10
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data = pd.read_csv('./data/barcelona_weekends.csv')
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data = pd.read_csv('./barcelona_weekends.csv')
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data = data.sample(cutoff)
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data = data.sample(cutoff)
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data = data.iloc[:, 1:]
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data = data.iloc[:, 1:]
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train_set, dev_set, test_set = np.split(data.sample(frac=1, random_state=42),
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train_set, dev_set, test_set = np.split(data.sample(frac=1, random_state=42),
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[int(.6 * len(data)), int(.8 * len(data))])
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[int(.6 * len(data)), int(.8 * len(data))])
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train_set.to_csv('data/barcelona_weekends.train.csv', index=False)
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train_set.to_csv('barcelona_weekends.train.csv', index=False)
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dev_set.to_csv('data/barcelona_weekends.dev.csv', index=False)
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dev_set.to_csv('barcelona_weekends.dev.csv', index=False)
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test_set.to_csv('data/barcelona_weekends.test.csv', index=False)
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test_set.to_csv('barcelona_weekends.test.csv', index=False)
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check = pd.read_csv('./train.csv')
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check = pd.read_csv('./train.csv')
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