Book Chapter10.1007/978-3-319-51969-2_21
Multiple Classification Using Logistic Regression Model
Baoping Zou
- 07 Dec 2016
- pp 238-243
4
TL;DR: This paper introduces how to adapt the traditional logistic regression model to multiple classification task, and the experimental results show that the proposed method is promising inmultiple classification task.
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Abstract: The traditional logistic regression model is always used binary classification tasks, such as a person’s gender (male or female). In this paper, we introduce how to adapt the traditional logistic regression model to multiple classification task. To validate our proposed method, we conduct an experiment on a open dataset, and the experimental results show that our proposed method is promising in multiple classification task.
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References
A review of goodness of fit statistics for use in the development of logistic regression models
Stanley Lemeshow,David W. Hosmer +1 more
TL;DR: Several statistics have recently been proposed for the purpose of assessing the goodness of fit of an estimated logistic regression model and one statistic is recommended for use and its computation is illustrated using data from a recent study of mortality of intensive care unit patients.
2K
Provision of Data-Intensive Services Through Energy- and QoS-Aware Virtual Machine Placement in National Cloud Data Centers
TL;DR: An improved particle swarm optimization algorithm is used to develop an optimal VM placement approach involving a tradeoff between energy consumption and global QoS guarantee for data-intensive services in NCDCs.
123
Cost-Aware Cloud Service Request Scheduling for SaaS Providers
TL;DR: A cost-aware service request scheduling approach based on genetic algorithm that can not only lease and reuse virtual resources on demand to achieve optimal scheduling of dynamic cloud service requests in reasonable time, but can also minimize the rental cost of the overall infrastructure for maximizing SaaS providers’ profits while meeting SLA constraints.
57
Reputation measurement of cloud services based on unstable feedback ratings
TL;DR: A lightweight reputation measurement approach for Cloud services based on (user) feedback ratings that is significantly effective for unstable feedback ratings and uses fuzzy set theory to calculate the reputation scores of Cloud services.
26
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