Add to ORKGAmong the different data mining techniques which can be used to extract knowledge from numerical data, the nearest neighbor approach has been widely applied in many mathematical and statistical problems. In this paper we use an algorithm based on a modified version of the nearest neighbor method to solve a problem of classifying the creditworthy clients, in a banking context. The empirical analysis is undertaken by considering data from an Italian local bank
The banking world in terms of lending to customers is routine activities that are at high risk. In i...
Data mining is a significant area for various commercial organizations comprising banking sector. It...
Objective: Assisting cooperatives in determining the classification of prospective financing members...
Among the different data mining techniques which can be used to extract knowledge from numerical dat...
Summarization: The classification problem consists of using some known objects, usually described by...
Data mining adalah teknik yang memanfaatkan data dalam jumlah yang besar untuk memperoleh informasi ...
Giving credit to customers is a solution that is often done by business actors today, such as compan...
AbstractIn this paper, a classification method named nearest subspace method is applied for credit r...
Abstract — Bank plays the central role for the economic development world-wide. The failure and succ...
International audienceThe application of classification models in the credit rating of banking custo...
Nowadays, the banking system is known as one of the inherent sectors of customer relationship manage...
The presence of machine learning, data mining and related disciplines is increasingly evident in eve...
One of the key elements in the banking industry rely on the appropriate selection of customers. In ...
In this paper a non-parametric statistical pattern recognition algorithm for the problem of credit s...
The article considers the binary classification problem of economic security objects on the credit i...
The banking world in terms of lending to customers is routine activities that are at high risk. In i...
Data mining is a significant area for various commercial organizations comprising banking sector. It...
Objective: Assisting cooperatives in determining the classification of prospective financing members...
Among the different data mining techniques which can be used to extract knowledge from numerical dat...
Summarization: The classification problem consists of using some known objects, usually described by...
Data mining adalah teknik yang memanfaatkan data dalam jumlah yang besar untuk memperoleh informasi ...
Giving credit to customers is a solution that is often done by business actors today, such as compan...
AbstractIn this paper, a classification method named nearest subspace method is applied for credit r...
Abstract — Bank plays the central role for the economic development world-wide. The failure and succ...
International audienceThe application of classification models in the credit rating of banking custo...
Nowadays, the banking system is known as one of the inherent sectors of customer relationship manage...
The presence of machine learning, data mining and related disciplines is increasingly evident in eve...
One of the key elements in the banking industry rely on the appropriate selection of customers. In ...
In this paper a non-parametric statistical pattern recognition algorithm for the problem of credit s...
The article considers the binary classification problem of economic security objects on the credit i...
The banking world in terms of lending to customers is routine activities that are at high risk. In i...
Data mining is a significant area for various commercial organizations comprising banking sector. It...
Objective: Assisting cooperatives in determining the classification of prospective financing members...