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Erschienen in:
2018 | OriginalPaper | Buchkapitel
Multiclass Data Classification Using Multinomial Logistic Gaussian Process Model
verfasst von : Wanhyun Cho, Soonyoung Park, Sangkyoon Kim
Erschienen in: Advances in Computer Science and Ubiquitous Computing
Verlag: Springer Singapore
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Abstract
We propose the multiclass data classification method using Bayesian logistic Gaussian process model. First, we have defined the multinomial logistic Gaussian process classification model. Second, we have derived the predictive distribution of the classification variable corresponding to the new input data point by using a variational Bayesian inference method. Finally, in order to verify the performance of the proposed model, we conducted experiments using Iris real dataset. From the experimental results, we can see that the proposed model has achieved superior classification ability.