Internal validation parameters of linear regression equations in QSAR problem
The article discusses a set of internal validation parameters that are (or can be) used to describe the quality of regression models in quantitative structure-activity relationship problems. Among these parameters there are well known determination coefficient, root mean square deviation, mean absol...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
V. N. Karazin Kharkiv National University
2023-05-01
|
| Series: | Вісник Харківського національного університету: Серія xімія |
| Subjects: | |
| Online Access: | https://periodicals.karazin.ua/chemistry/article/view/23245 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1841549922971680768 |
|---|---|
| author | Inna Khristenko Volodymyr Ivanov |
| author_facet | Inna Khristenko Volodymyr Ivanov |
| author_sort | Inna Khristenko |
| collection | DOAJ |
| description | The article discusses a set of internal validation parameters that are (or can be) used to describe the quality of regression models in quantitative structure-activity relationship problems. Among these parameters there are well known determination coefficient, root mean square deviation, mean absolute error, etc. Also the indices based at Kullback-Leibler divergence as a measure of distance between two sets have been investigated. All the parameters (indices) were calculated for several regression models which describe boiling point of saturated hydrocarbons (alkanes). Regression models include a four-component additive scheme and equations describing the property as a function of topological indices. The two types of regressions based on these indices are linear dependencies on only one topological index and linear dependencies on topological index and the number of carbon atoms in the hydrocarbon. Various linear regression equations have been described with internal validation parameters that evaluate the quality of the equations from different perspectives. It is shown that a wide set of test parameters is not only an additional yet alternative description of regression models, but also provides the most complete description of the predictive characteristics and quality of the obtained regression model. |
| format | Article |
| id | doaj-art-559796a2220a4aff850597c0e9845505 |
| institution | Kabale University |
| issn | 2220-637X 2220-6396 |
| language | English |
| publishDate | 2023-05-01 |
| publisher | V. N. Karazin Kharkiv National University |
| record_format | Article |
| series | Вісник Харківського національного університету: Серія xімія |
| spelling | doaj-art-559796a2220a4aff850597c0e98455052025-01-10T11:26:48ZengV. N. Karazin Kharkiv National UniversityВісник Харківського національного університету: Серія xімія2220-637X2220-63962023-05-0140122110.26565/2220-637X-2023-40-0223245Internal validation parameters of linear regression equations in QSAR problemInna Khristenko0Volodymyr Ivanov1V. N. Karazin Kharkiv National University, 4 Svobody sq., Kharkiv, 61022, UkraineV. N. Karazin Kharkiv National University, 4 Svobody sq., Kharkiv, 61022, UkraineThe article discusses a set of internal validation parameters that are (or can be) used to describe the quality of regression models in quantitative structure-activity relationship problems. Among these parameters there are well known determination coefficient, root mean square deviation, mean absolute error, etc. Also the indices based at Kullback-Leibler divergence as a measure of distance between two sets have been investigated. All the parameters (indices) were calculated for several regression models which describe boiling point of saturated hydrocarbons (alkanes). Regression models include a four-component additive scheme and equations describing the property as a function of topological indices. The two types of regressions based on these indices are linear dependencies on only one topological index and linear dependencies on topological index and the number of carbon atoms in the hydrocarbon. Various linear regression equations have been described with internal validation parameters that evaluate the quality of the equations from different perspectives. It is shown that a wide set of test parameters is not only an additional yet alternative description of regression models, but also provides the most complete description of the predictive characteristics and quality of the obtained regression model.https://periodicals.karazin.ua/chemistry/article/view/23245quantitative structure-activity relationships (qsar)regression modelsinternal validationtopological descriptors |
| spellingShingle | Inna Khristenko Volodymyr Ivanov Internal validation parameters of linear regression equations in QSAR problem Вісник Харківського національного університету: Серія xімія quantitative structure-activity relationships (qsar) regression models internal validation topological descriptors |
| title | Internal validation parameters of linear regression equations in QSAR problem |
| title_full | Internal validation parameters of linear regression equations in QSAR problem |
| title_fullStr | Internal validation parameters of linear regression equations in QSAR problem |
| title_full_unstemmed | Internal validation parameters of linear regression equations in QSAR problem |
| title_short | Internal validation parameters of linear regression equations in QSAR problem |
| title_sort | internal validation parameters of linear regression equations in qsar problem |
| topic | quantitative structure-activity relationships (qsar) regression models internal validation topological descriptors |
| url | https://periodicals.karazin.ua/chemistry/article/view/23245 |
| work_keys_str_mv | AT innakhristenko internalvalidationparametersoflinearregressionequationsinqsarproblem AT volodymyrivanov internalvalidationparametersoflinearregressionequationsinqsarproblem |