عنوان المقالة: Predicting reaction based on customer's transaction using machine learning approaches
حسين عبد الكريم يونس | hussain A.younis | 6010
نوع النشر
مجلة علمية
المؤلفون بالعربي
إسراء محمد حيدر، غزوان عبد النبي العلي، حسين عبد الله يونس
المؤلفون بالإنجليزي
Israa M. Hayder, Ghazwan Abdul Nabi Al Ali, Hussain A. Younis
الملخص الانجليزي
Banking advertisements are important because they help target specific customers on subscribing to their packages or other deals by giving their current customers more fixed-term deposit offers. This is done through promotional advertisements on the Internet or media pages, and this task is the responsibility of the shopping department. In order to build a relationship with them, offer them the best deals, and be appropriate for the client with the company's assurance to recover these deposits, many banks or telecommunications firms store the data of their customers. The Portuguese bank increases its sales by establishing a relationship with its customers. This study proposes creating a prediction model using machine learning algorithms, to see how the customer reacts to subscribe to those fixed-term deposits or offers made with the aid of their past record. This classification is binary, ie, the prediction of whether or not a customer will embrace these offers. Four classifiers that include k-nearest neighbor (k-NN) algorithm, decision tree, naive Bayes, and support vector machines (SVM) were used, and the best result was obtained from the classifier decision tree with an accuracy of 91% and the other classifier SVM with an accuracy of 89%.
تاريخ النشر
22/09/2023
الناشر
International Journal of Electrical and Computer Engineering
رقم المجلد
13
رقم العدد
1
ISSN/ISBN
ISSN: 2088-8708
رابط DOI
DOI: 10.11591/ijece.v13i1.pp1086-1096
الصفحات
1086-1096
رابط الملف
تحميل (1 مرات التحميل)
الكلمات المفتاحية
Bank marketing Decision tree K-nearest neighbors’ algorithm Naive Bayes Support vector machines
رجوع