Pretražite po imenu i prezimenu autora, mentora, urednika, prevoditelja

Napredna pretraga

Pregled bibliografske jedinice broj: 868943

The difference between the accuracy of real and the corresponding random model is a useful parameter for validation of two-state classification model quality


Batista, Jadranko; Vikić-Topić, Dražen; Lučić, Bono
The difference between the accuracy of real and the corresponding random model is a useful parameter for validation of two-state classification model quality // Croatica chemica acta, 89 (2016), 4; 527-534 doi:10.5562/cca3117 (međunarodna recenzija, članak, znanstveni)


CROSBI ID: 868943 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
The difference between the accuracy of real and the corresponding random model is a useful parameter for validation of two-state classification model quality

Autori
Batista, Jadranko ; Vikić-Topić, Dražen ; Lučić, Bono

Izvornik
Croatica chemica acta (0011-1643) 89 (2016), 4; 527-534

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
classification model ; Q2 accuracy ; overall classification accuracy ; random classification accuracy ; classification accuracy difference ; correct class estimation ; under-prediction ; over-prediction ; class imbalance ; membrane structure modeling ; QSAR classification modeling

Sažetak
The simplest and the most commonly used measure for assess the classification model quality is parameter Q2 = 100 (p + n) / N (%) named the classification accuracy, p, n and N are the total numbers of correctly predicted compounds in the first and in the second class, and the total number of elements of classes (compounds) in data set, respectively. Moreover, the most probable accuracy that can be obtained by a random model is calculated for two-state model by the formulae Q2, rnd = 100 [(p + u) (p + o) + (n + u) (n + o)] / N2 (%), where u and o are the total number of under- predictions (when class 1 is predicted by the model as class 2) and over-predictions (when class 2 is predicted by the model as class 1) in data set, respectively. Finally, the difference between these two parameter ΔQ2 = Q2 – Q2, rnd is introduced, and it is suggested to compute and give ΔQ2 for each two-state classification model to assess its contribution over the accuracy of the corresponding random model. When data set is ideally balanced having the same numbers of elements in both classes, the two-state classification problem is the most difficult with maximal Q2 = 100 % and Q2, rnd = 50 %, giving the maximal ΔQ2 = 50 %. The usefulness of ΔQ2 parameter is illustrated in comparative analysis on two-class classification models from literature for prediction of secondary structure of membrane proteins and on several quanti¬tative structure- property models. Real contributions of these models over the random level of accuracy is calculated, and their ΔQ2 values are compared mutually and with the value of ΔQ2 (= 50 %) for the most difficult two-state classification model.

Izvorni jezik
Engleski

Znanstvena područja
Fizika, Kemija



POVEZANOST RADA


Projekt / tema
098-1770495-2919 - Razvoj metoda za modeliranje svojstava bioaktivnih molekula i proteina (Bono Lučić, )

Ustanove
Institut "Ruđer Bošković", Zagreb

Profili:

Avatar Url Bono Lučić (autor)

Avatar Url Dražen Vikić-Topić (autor)

Citiraj ovu publikaciju

Batista, Jadranko; Vikić-Topić, Dražen; Lučić, Bono
The difference between the accuracy of real and the corresponding random model is a useful parameter for validation of two-state classification model quality // Croatica chemica acta, 89 (2016), 4; 527-534 doi:10.5562/cca3117 (međunarodna recenzija, članak, znanstveni)
Batista, J., Vikić-Topić, D. & Lučić, B. (2016) The difference between the accuracy of real and the corresponding random model is a useful parameter for validation of two-state classification model quality. Croatica chemica acta, 89 (4), 527-534 doi:10.5562/cca3117.
@article{article, year = {2016}, pages = {527-534}, DOI = {10.5562/cca3117}, keywords = {classification model, Q2 accuracy, overall classification accuracy, random classification accuracy, classification accuracy difference, correct class estimation, under-prediction, over-prediction, class imbalance, membrane structure modeling, QSAR classification modeling}, journal = {Croatica chemica acta}, doi = {10.5562/cca3117}, volume = {89}, number = {4}, issn = {0011-1643}, title = {The difference between the accuracy of real and the corresponding random model is a useful parameter for validation of two-state classification model quality}, keyword = {classification model, Q2 accuracy, overall classification accuracy, random classification accuracy, classification accuracy difference, correct class estimation, under-prediction, over-prediction, class imbalance, membrane structure modeling, QSAR classification modeling} }

Časopis indeksira:


  • Current Contents Connect (CCC)
  • Web of Science Core Collection (WoSCC)
    • Science Citation Index Expanded (SCI-EXP)
    • SCI-EXP, SSCI i/ili A&HCI


Citati