Establishment of Elimination Method of Outliers Based on Grubbs Rule and MATLAB Language and Its Application in Ev- aluating Drug Bitterness
- VernacularTitle:基于Grubbs规则和MATLAB语言快速剔除异常值方法的建立及其在药物苦度评价中的应用
- Author:
Ruixin LIU
1
,
2
,
3
,
4
;
Yanli WANG
3
;
Yao ZHANG
3
;
Xinjing GUI
1
,
2
;
Junming WANG
3
;
Qingxiao WANG
5
;
Jing YAO
1
,
2
;
Lu ZHANG
1
,
2
;
Junhan SHI
1
,
2
;
Xuelin LI
1
,
2
,
3
Author Information
1. Dept. of Pharmacy，the First Affiliated Hospital of Henan University of TCM，Zhengzhou 450000，China
2. Third-level Laboratory of TCM Preparation，State Administration of TCM，Zhengzhou 450000，China
3. College of Pharmacy，Henan University of TCM，Zhengzhou 450008，China
4. Henan Collaborative Innovation Center for Respiratory Disease Diagnosis and Treatment and New Drug R&D，Zhengzhou 450000，China
5. Henan Provincial Institute of Food and Drug Control，Zhengzhou 450000，China
- Publication Type:Journal Article
- Keywords:
Grubbs rule;
MATLAB language;
Outliers;
Elimination;
Medicinal material;
Bitterness evaluation
- From:
China Pharmacy
2019;30(2):176-182
- CountryChina
- Language:Chinese
-
Abstract:
OBJECTIVE： To establish the elimination method of outliers based on Grubbs rule and MATLAB language， and to evaluate the effects of it on drug bitterness evaluation. METHODS： Referring to Grubbs rule， the automatic cyclic outliers elimination method based on MATLAB language was established. Totally 20 volunteers were included in single oral taste test （Tetrapanax papyrifer） and multiple oral taste test （10 kinds of medicinal material as T. papyrifer， Changium smyrnioides， Poria cocos， etc.）. Seven sensors were selected for electronic tongue test （Clematis armandii）. The data of bitterness evaluation in above tests （oral taste test as bitterness value， electronic tongue test as response value of sensors） were used as the data source. Five researchers were selected and adopted table-by-table elimination method based on Grubbs rule （method one）， Excel software elimination method based on Grubbs rule （method two） and automatic cyclic outliers elimination method based on Grubbs rule and MATLAB language （method three） to judge and eliminate the outliers. The effects of above three methods were evaluated with the removal time and error rate of outliers as indexes. RESULTS： There were two outliers in the data of bitterness evaluation in single oral taste test； the elimination time of the three methods were（745.400 0±25.904 4），（288.333 3±31.253 1）and（0.000 3±0.000 0）s， respectively； error rates were 20.0％， 0 and 0， respectively. There were six outliers in the data of bitterness evaluation in multiple oral taste test； the elimination time of three methods were （3 693.107 7±75.023 3）， （1 494.761 4±53.826 9）， （0.005 2±0.000 0）s， respectively； error rates were 10.0％， 4.0％， 0， respectively. There were three outliers in the data of bitterness evaluation in electronic tongue test； the elimination time of three methods were （2 992.673 3±84.117 6）， （1 276.367 1±55.024 5）， （0.002 3±0.000 0）s， respectively； error rates were 5.7％， 2.9％， 0， respectively. The elimination results of the three methods were consistent. The elimination time of method two was significantly shorter than that of method one （P＜0.01）； the elimination time of method three was significantly shorter than those of method one and method two （P＜0.01）. There was no significant difference in error rate of 3 methods （P＞0.05）. CONCLUSIONS： The automatic cyclic elimination method of outliers based on Grubbs rule and MATLAB language can significantly shorten the elimination time of outliers in data of drug bitterness evaluation， improve the efficiency of data processing， and is suitable for drug bitterness evaluation.
