In this paper, a model combining recurrent neural networks and convolutional neural networks is proposed to build a model that can simultaneously estimate missing values and classify time series data. The experimental results demonstrate that the proposed model performs better than the existing methods for time series classification with incomplete data.
Nội dung trích xuất từ tài liệu:
Deep learning for simultaneous imputation and classification of time series incomplete data
Deep learning for simultaneous imputation and classification of time series incomplete data
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Tìm kiếm theo từ khóa liên quan:
Practical applications Deep learning Simultaneous imputation Neural networks Building classification modelsTài liệu có liên quan:
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