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on 05-Nov-2025 (Wed)

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Flashcard 7766918434060

Tags
#feature-engineering #lstm #recurrent-neural-networks #rnn
Question
To increase the match of the model's effective capacity and the complexity of the task at hand, the analyst needs to tune both the parameters and the hyperparameters of the model. Given how sensitive LSTM models are to [...] tuning, this area requires particular attention.
Answer
hyperparameter

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the model's effective capacity and the complexity of the task at hand, the analyst needs to tune both the parameters and the hyperparameters of the model. Given how sensitive LSTM models are to <span>hyperparameter tuning, this area requires particular attention. <span>

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Flashcard 7767419915532

Tags
#has-images #recurrent-neural-networks #rnn
[unknown IMAGE 7101515435276]
Question
Fig. 2. The structure of the model begins with its input layers for (i) the input variable (i.e., transaction counts) and (ii) [...] covariates (time-invariant or time-varying inputs)
Answer
optional

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Fig. 2. The structure of the model begins with its input layers for (i) the input variable (i.e., transaction counts) and (ii) optional covariates (time-invariant or time-varying inputs)

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Flashcard 7767423585548

Tags
#deep-learning #keras #lstm #python #sequence
Question
For a [...] classification problem, the predictions may be an array of probabilities for the first class that can be converted to a 1 or 0 by rounding
Answer
binary

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For a binary classification problem, the predictions may be an array of probabilities for the first class that can be converted to a 1 or 0 by rounding

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