da15160c068d5ffd9ff8fd2fae06a5a3e08cece3,lexos/processors/analyze/information.py,CorpusInformation,__init__,#CorpusInformation#Any#Any#,11
Before Change
file_anomaly_std_err = {}
file_anomaly_iqr = {}
file_sizes = {}
for i in range(num_file):
file_sizes.update({l_files[i]: sum(word_lists[i].values())})
file_sizes_list = list(file_sizes.values())
// TODO: Correct the way to find standard error
// 1 standard error analysis
After Change
file_sizes = np.sum(count_matrix, axis=1)
// TODO: Correct the way to find standard error
// 1 standard error analysis
average_file_size = np.average(file_sizes)
// Calculate the standard deviation
std_dev_file_size = np.std(file_sizes)
// Calculate the anomaly
for count, label in enumerate(labels):
In pattern: SUPERPATTERN
Frequency: 3
Non-data size: 5
Instances Project Name: WheatonCS/Lexos
Commit Name: da15160c068d5ffd9ff8fd2fae06a5a3e08cece3
Time: 2017-07-26
Author: weltch1997@gmail.com
File Name: lexos/processors/analyze/information.py
Class Name: CorpusInformation
Method Name: __init__
Project Name: tgsmith61591/pmdarima
Commit Name: bc4a5f5d29bb5a74d9cb254ff4dfed916676c8aa
Time: 2019-11-01
Author: tgsmith61591@gmail.com
File Name: examples/model_selection/example_cross_validation.py
Class Name:
Method Name:
Project Name: automl/auto-sklearn
Commit Name: b53c7e1fc510eaa3154c933e549de1580425a144
Time: 2018-12-06
Author: 31531627+ahn1340@users.noreply.github.com
File Name: autosklearn/ensembles/ensemble_selection.py
Class Name: EnsembleSelection
Method Name: predict