Discretization: An Enabling Technique
Data Mining and Knowledge Discovery
A Modified Chi2 Algorithm for Discretization
IEEE Transactions on Knowledge and Data Engineering
On Changing Continuous Attributes into Ordered Discrete Attributes
EWSL '91 Proceedings of the European Working Session on Machine Learning
Chi2: Feature Selection and Discretization of Numeric Attributes
TAI '95 Proceedings of the Seventh International Conference on Tools with Artificial Intelligence
Toward Unsupervised Correlation Preserving Discretization
IEEE Transactions on Knowledge and Data Engineering
CD: a coupled discretization algorithm
PAKDD'12 Proceedings of the 16th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part II
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The mobile market is becoming more competitive. Mobile operators having been focusing on the market share of high quality customers. In this paper, we propose a new method to help mobile operator to estimate the share in high quality customers market based on the available data, inter-network calling detail records. The core of our method is a discretization algorithm which adopts the Gini criterion as discretization measure and is supervised, global and static. In order to evaluate the model, we use the real life data come from one mobile operator in China mainland. The results prove that our method is effective. And also our method is simple and easy to be incorporated into operation support system to predict periodically