Description
Abstract ( 1 Page )
Introduction/Background work on Bank marketing ( 2 page )
Models:
-> KNN (k-nearest neighbors algorithm) ( 1 page )
Conclusion
Reference
Explanation & Answer
Attached.
CLASSIFICATION MODELS ON BANK MARKETING
Name
Classification Models On Bank Marketing
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CLASSIFICATION MODELS ON BANK MARKETING
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Classification Models On Bank Marketing
Abstract
Every marketing campaign is dependent on the data provided by its clients. This data
comprises information related to the names of clients, their numbers, salary, the loans taken by
them, the money in their account etc. These are huge datasets, and for a human, it is not possible
to examine the client deposits’ patterns and whether or not there would be a successful
campaign. In the current study, the classification method of k-Nearest Neighbor is going to be
discussed. Because of the impacts of financial distress of the companies on stakeholders, models
of financial distress forecast have been the most attractive field within financial research. After
the international monetary crisis in recent years, the number of the bankrupt organization has
increased. Since financial distress of the organizations is the bankruptcy’s first stage, using
monetary ratios for forecasting financial suffering, have involved too much attention of the
academics, along with financial and economic institutions. The focus of this paper is on bank
marketing models, especially the focus of the paper is on the k-Nearest Neighbor algorithm.
Keywords: k-Nearest Neighbor algorithm, Bank Marketing,
CLASSIFICATION MODELS ON BANK MARKETING
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Classification Models On Bank Marketing
Introduction/Background work on Bank Marketing
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