Ant Colony Optimization Algorithms in the Problem of Predicting the Efficiency of the Bank Telemarketing Campaign

In this article, we analyze the effectiveness of the telemarketing campaign developed by the Portuguese bank. The main goal of this analysis was to estimate, is there existing ant colony algorithms are capable of building classifiers that lead to increasing the effectiveness of the telemarketing campaign. An additional question was related to the problem of adjusting the whole campaign to the actual needs of clients. Presented data include 17 attributes, including information about the efficiency of carried out conversations related to the bank deposit offer. The analysis presented in this article was developed on the basis of algorithms used for the decision trees construction such as CART and C4.5. As a result, a prediction allowing to estimate the result of the telemarketing conversation with a client was made. Conducted experiments allowed for the comparison of different classifiers. The comparison was made on the basis of different measures of classification efficiency. It is especially important in the case of the real-world data, where cardinality of decision classes is uneven. Conducted experiments allowed for the comparison of different classifiers. Initial evaluation confirms, that such an approach could be efficiently used for the dynamic data sets, like streams.