d194d8abd924932caab53d6e858918a84f3e5b64,brats/evaluate.py,,main,#,27
Before Change
df = pd.DataFrame.from_records(rows, columns=header)
df.to_csv("./prediction/brats_scores.csv")
plt.boxplot(df.values, labels=df.columns)
plt.ylabel("Dice Coefficient")
plt.savefig("validation_scores_boxplot.png")
plt.close()
After Change
scores = dict()
for index, score in enumerate(df.columns):
values = df.values.T[index]
scores[score] = values[np.isnan(values) == False]
plt.boxplot(list(scores.values()), labels=list(scores.keys()))
plt.ylabel("Dice Coefficient")
In pattern: SUPERPATTERN
Frequency: 3
Non-data size: 3
Instances
Project Name: ellisdg/3DUnetCNN
Commit Name: d194d8abd924932caab53d6e858918a84f3e5b64
Time: 2017-12-18
Author: david.ellis@unmc.edu
File Name: brats/evaluate.py
Class Name:
Method Name: main
Project Name: dirty-cat/dirty_cat
Commit Name: f819a34e2fbea2dab4997b3b236b517fa12d115d
Time: 2018-06-08
Author: gael.varoquaux@normalesup.org
File Name: examples/03_midwest_survey.py
Class Name:
Method Name:
Project Name: dirty-cat/dirty_cat
Commit Name: f819a34e2fbea2dab4997b3b236b517fa12d115d
Time: 2018-06-08
Author: gael.varoquaux@normalesup.org
File Name: examples/02_predict_employee_salaries.py
Class Name:
Method Name: