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Karolina Oparczyk 2021-05-20 19:50:46 +02:00
parent b9f143d46c
commit 8251db9abf
3 changed files with 16 additions and 6 deletions
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1
Dockerfile
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@ -8,6 +8,7 @@ RUN pip3 install pandas
RUN pip3 install kaggle
RUN pip3 install tensorflow
RUN pip3 install sklearn
RUN pip3 install matplotlib
COPY ./data_dev ./
COPY ./evaluate_network.py ./
RUN mkdir /.kaggle

2
JenkinsfileEval
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@ -19,7 +19,7 @@ node {
}
stage('Clone repo') {
docker.image("karopa/ium:16").inside {
docker.image("karopa/ium:20").inside {
stage('Test') {
checkout([$class: 'GitSCM', branches: [[name: '*/evaluation']], doGenerateSubmoduleConfigurations: false, extensions: [], submoduleCfg: [], userRemoteConfigs: [[url: 'https://git.wmi.amu.edu.pl/s434765/ium_434765']]])
copyArtifacts fingerprintArtifacts: true, projectName: 's434765-create-dataset', selector: buildParameter("BUILD_DATASET")

19
evaluate_network.py
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@ -2,15 +2,16 @@ import pandas as pd
import numpy as np
from sklearn.metrics import mean_squared_error
from tensorflow import keras
import matplotlib.pyplot as plt
model = keras.models.load_model('model')
data = pd.read_csv("data_dev", sep=',', error_bad_lines=False,
skip_blank_lines=True, nrows=527, names=["video_id", "last_trending_date",
"publish_date", "publish_hour", "category_id",
"channel_title", "views", "likes", "dislikes",
"comment_count"]).dropna()
X_test = data.loc[:,data.columns == "views"].astype(int)
y_test = data.loc[:,data.columns == "likes"].astype(int)
"publish_date", "publish_hour", "category_id",
"channel_title", "views", "likes", "dislikes",
"comment_count"]).dropna()
X_test = data.loc[:, data.columns == "views"].astype(int)
y_test = data.loc[:, data.columns == "likes"].astype(int)
min_val_sub = np.min(X_test)
max_val_sub = np.max(X_test)
@ -39,3 +40,11 @@ print(error)
with open("rmse.txt", "a") as file:
file.write(str(error) + "\n")
with open("rmse.txt", "r") as file:
lines = file.readlines()
plt.plot(range(len(lines)), [line[:-2] for line in lines])
plt.tight_layout()
plt.ylabel('RMSE')
plt.xlabel('evaluation no')
plt.savefig('evaluation.png')