TY  - JOUR
T1  - DIVORCE PREDICTION USING CORRELATION BASED FEATURE SELECTION AND ARTIFICIAL NEURAL NETWORKS
AU  - Yöntem, Mustafa Kemal
AU  - Adem, Kemal
AU  - İlhan, Tahsin
AU  - Kılıçarslan, Serhat
PY  - 2019
DA  - June
JF  - Nevşehir Hacı Bektaş Veli Üniversitesi SBE Dergisi
PB  - Nevşehir Hacı Bektaş Veli Üniversitesi
WT  - DergiPark
SN  - 2149-3871
SP  - 259
EP  - 273
VL  - 9
IS  - 1
LA  - tr
AB  - Within the scope of this research,the divorce prediction was carried out by using the Divorce Predictors Scale(DPS) on the basis of Gottman couplestherapy. Of the participants, 84 (49%) were divorced and 86 (51%) were marriedcouples. Participants completed the “PersonalInformation Form” and “Divorce Predictors Scale”. In this study, the success ofDPS, was investigated using Multilayer Perceptron Neural Network and C4.5Decision tree algorithms. In addition, the study also aims to find the mostsignificant features/items in the Divorce Predictors Scale that affect thedivorce. The most effective 6features and their values of significance obtained by applying thecorrelation-based feature selection method on the divorce data set. When we look at these features, they arerelated to creating a common meaning and failed attempts to repair, love mapand negative conflict behaviors. When the direct classification methods were applied to the divorce dataset, the highest success rate was 98.23% obtained with the RBF neural network.After selecting the most effective 6 features using the correlation-basedfeature selection method on the same data set, the highest accuracy rateobtained was 98.82% with ANN. According to the results, DPS can predictdivorce. Family counselors and family therapists can use this scale forcontribute to the preparation of case formulation and intervention plan. Alsoit can be said that the divorce predictors in the Gottman couples therapy wereconfirmed in the Turkish sampling.
KW  - Data mining
KW  - artificial neural networks
KW  - divorce
KW  - divorce prediction
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UR  - http://dergipark.org.tr/tr/pub/nevsosbilen/issue//549416
L1  - http://dergipark.org.tr/tr/download/article-file/748448
ER  -