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Add plot

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This commit is contained in:
PawelDopierala 2024-05-15 00:22:12 +02:00
parent 24415420c5
commit 9b029d71a9
4 changed files with 20 additions and 17 deletions
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4
Dockerfile
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@ -2,7 +2,7 @@ FROM ubuntu:latest
RUN apt-get update && \ RUN apt-get update && \
apt-get install -y python3-pip && \ apt-get install -y python3-pip && \
pip3 install kaggle pandas scikit-learn tensorflow pip3 install kaggle pandas scikit-learn tensorflow matplotlib
RUN useradd -ms /bin/bash jenkins RUN useradd -ms /bin/bash jenkins
@ -13,6 +13,6 @@ USER jenkins
COPY data_processing.py . COPY data_processing.py .
COPY create_model.py . COPY create_model.py .
COPY helper.py . COPY helper.py .
COPY predict_price.py . COPY evaluate.py .
WORKDIR . WORKDIR .

2
JenkinsfileEvaluation
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@ -51,7 +51,7 @@ pipeline {
} }
stage('CreateArtifacts') { stage('CreateArtifacts') {
steps { steps {
archiveArtifacts artifacts: 'hp_test_predictions.csv,hp_test_metrics.csv' archiveArtifacts artifacts: 'hp_test_predictions.csv,hp_test_metrics.csv,metrics_plt.png'
} }
} }
} }

18
evaluate.py
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@ -5,6 +5,7 @@ import os
from sklearn.metrics import mean_squared_error, mean_absolute_error, r2_score from sklearn.metrics import mean_squared_error, mean_absolute_error, r2_score
from keras.models import load_model from keras.models import load_model
from helper import prepare_tensors from helper import prepare_tensors
import matplotlib.pyplot as plt
build_number = int(sys.argv[1]) build_number = int(sys.argv[1])
@ -36,4 +37,19 @@ if os.path.isfile(metrics_file):
else: else:
updated_metrics_df = metrics_df updated_metrics_df = metrics_df
updated_metrics_df.to_csv(metrics_file, index=False) updated_metrics_df.to_csv(metrics_file, index=False)
plt.figure(figsize=(10, 6))
plt.plot(updated_metrics_df['Build_Number'], updated_metrics_df['RMSE'], label='RMSE', marker='o')
plt.plot(updated_metrics_df['Build_Number'], updated_metrics_df['MAE'], label='MAE', marker='o')
plt.plot(updated_metrics_df['Build_Number'], updated_metrics_df['R2'], label='R2', marker='o')
plt.title('Metrics vs Builds')
plt.xlabel('Build Number')
plt.ylabel('Metric Value')
plt.legend()
plt.grid(True)
plot_file = 'metrics_plt.png'
plt.savefig(plot_file)
plt.close()

13
predict_price.py
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@ -1,13 +0,0 @@
import pandas as pd
from keras.models import load_model
from helper import prepare_tensors
hp_test = pd.read_csv('hp_test.csv')
X_test, Y_test = prepare_tensors(hp_test)
model = load_model('hp_model.h5')
test_predictions = model.predict(X_test)
predictions_df = pd.DataFrame(test_predictions, columns=["Predicted_Price"])
predictions_df.to_csv('hp_test_predictions.csv', index=False)