[Matlab] Data classification prediction based on long short-term memory network (Excel can directly replace data)
1. Model Principle
"Data classification prediction based on long-term short-term memory network" is a method of using long-term short-term memory network (Long Short-Term Memory, LSTM) for data classification tasks. LSTM is a special kind of Recurrent Neural Network (RNN) that can efficiently process sequence data and perform well for long-term dependency problems. In the data classification prediction task, the LSTM network can receive sequential data as input and map it to the corresponding category.
The following is the principle of "data classification prediction based on long short-term memory network":
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Introduction to Long Short-Term Memory Network (LSTM) :
LSTM is a special RNN designed to solve the problem of gradient disappearance or gradient explosion that is prone to occur when traditional RNNs process long sequences. LSTM introduces a concept called "Cell State" and controls the flow of information through gating cells. LSTM has three gating units: input gate (Input Gate), forget gate (Forget Gate) and output gate (Ou