Oct 18, 2023 · This paper uses LSTM to design a feature selection method termed FSLSTM (Feature Selection using LSTM) to select discriminative terms for high-dimensional text ...

Oct 18, 2023 · The proposed method extends the limitation of term frequency information by applying deep features for feature selection. Experiments in nine ...

Feature selection based on long short term memory for text classification ... document frequency based feature selection metrics in text categorization ...

Feb 21, 2022 · In this paper, an evolving LSTM (ELSTM) network is proposed. A multiobjective genetic algorithm (MOGA) is used to optimize the architecture and weights of LSTM.

Feature selection based on long short term memory for text classification. Ming Hong,. Heyong Wang. Help me understand this report.

LSTM stands for long-short term memory. This article explains what is LSTM Python and how can LSTM used for Text Classification.

In the classification of traditional algorithms, problems of high features dimension and data sparseness often occur when classifying text.

May 30, 2024 · In this study, we used unidirectional and bidirectional long short-term memory (LSTM) deep learning networks for Chinese news classification.

The selection of discriminative terms from large quantity of terms in text documents is helpful for achieving better accuracy of text classification.

In this paper, we present an in-depth comparative study on these two types of approaches, feature selection based approaches and and deep learning models for ...