Συστήματα Υποαστήριξης Απόφασης για την πρόβλεψη τραπεζικού marketing
Date Issued
June 17, 2020
Type
Πτυχιακή Εργασία
Abstract
The topic of my task is "Decision Support Systems for Banking Marketing Forecasting". My thesis focuses on finding the best model for the effectiveness of banking marketing. The finding of this model is done through the study and processing of the data set of the UCI bank telemarketing data set (with 45211 data and 17
categories). The Weka data mining tool was used to process the above data. Regarding the evaluation of the data, this was achieved with various algorithms such as (C4.5, Naive Bayes, Random Forest, Logistic Regression). Data analysis was done in two categories: imbalanced data and balanced data. Moreover, feature selection was used for the best possible attribute selection. However, in addition to processing the data to find the best possible model in our research, we also analyzed the work of a similar subject in order to be able to study other ways of data processing in the same or similar data sets, but also to see other results and to compare them with our own.
Subjects