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Table8. PredictionAccuracyComparisonofFiveModels.
NO. Model Accuracy NO. Model Accuracy
1 SVM 0.650 4 LSTM 0.625
2 GBDT 0.683 5 Perceptron 0.945
3 XGBoost 0.740
accuracy is not high.At the same time, it can also be concluded thatwhen choosing a
widevariety of complexmachine learning, the specific choice ofwhatmethoddepends
on the size of thedataset and the complexity of theproblem itself. In the experiment of
thispaper, theeffectof simpleperceptron is themost effective.
The following is a detailed introduction to the experimental situationof the simple
perceptron, and the test resultsof theperceptronare shown inTable9.
The ‘before’ column indicates that themodel only uses structureddata for training
andtesting,and its testingaccuracy is92.5%; the‘after’columnrepresents thecombina-
tionof structureddata, news text data anddefinedKeywordGroups (Table 6), and then
training and testingwith an accuracy of 94.5%. It can be seen that adding unstructured
textdatawill behelpful in improvingaccuracy.
Table9. PredictingResultsofPerceptron.
NO. before after NO. before after
1 0.92792793 0.95495495 6 0.927927928 0.954954955
2 0.92792792 0.936936937 7 0.90990991 0.927927929
3 0.90990991 0.963963965 8 0.918918919 0.945945948
4 0.927927928 0.936936937 9 0.927927928 0.945945947
5 0.936936937 0.936936938 10 0.936936937 0.945945946
Average 0.925225225 0.945045045
Thefollowingisadeterminationof theprosandconsof themodel throughtheROC
(Receiver Operating Characteristic) curve, which is often used to evaluate the merits
of aBinaryClassifier [11]. As can be seen fromFig.2, theROCcurve (before) of one
classifier is completely ‘below’ the curve (after) of another [12], then it canbe asserted
that the performance of the latter is better than the former, that is, by adding the news
text caneffectively improve theaccuracyof thepredict.
7. Conclusion
In thispaper, inorder to improve theaccuracyofpredicting the levelofcapitaladequacy
ofcommercialbanks,worksare summarizedas follows:
• Thecombinationof structuredandunstructureddata.
• Themethodofextractingkeyword features.
• Multiplemodel comparisonandselection.
The average accuracy rate of predicting the level of capital adequacy of the com-
mercialbank in thenext sevendays ismore than94.5%,whichproves thevalidityof the
model.
Y.Duetal. /Predicting the
InterbankCapitalAdequacyLevelBasedonFinancialDataAnalysis44
Intelligent Environments 2019
Workshop Proceedings of the 15th International Conference on Intelligent Environments
- Titel
- Intelligent Environments 2019
- Untertitel
- Workshop Proceedings of the 15th International Conference on Intelligent Environments
- Autoren
- Andrés Muñoz
- Sofia Ouhbi
- Wolfgang Minker
- Loubna Echabbi
- Miguel Navarro-Cía
- Verlag
- IOS Press BV
- Datum
- 2019
- Sprache
- deutsch
- Lizenz
- CC BY-NC 4.0
- ISBN
- 978-1-61499-983-6
- Abmessungen
- 16.0 x 24.0 cm
- Seiten
- 416
- Kategorie
- Tagungsbände