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on 01-Feb-2026 (Sun)

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Flashcard 7789521014028

Tags
#feature-engineering #lstm #recurrent-neural-networks #rnn
Question
models with high capacity may overfit the training set and exhibit [...] variance
Answer
high

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models with high capacity may overfit the training set and exhibit high variance

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Annotation 7793993714956

#deep-learning #keras #lstm #python #sequence
Think of the internal state of LSTMs as a handy internal variable to capture and provide context for making predictions
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Think of the internal state of LSTMs as a handy internal variable to capture and provide context for making predictions. If your problem looks like a traditional autoregression type problem with the most relevant lag observations within a small window, then perhaps develop a baseline of performance with

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Flashcard 7793998433548

Tags
#feature-engineering #lstm #recurrent-neural-networks #rnn
Question
link donors' first names to the [...] of said first names in the population to infer donors' age
Answer
average age pyramid

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link donors' first names to the average age pyramid of said first names in the population to infer donors' age

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Flashcard 7794000530700

Question
3. Ambiguous: Surveys often fail to reveal the [...] of customer sentiment. In fact, scores can vary based on many outside factors, including geographical bias and industry shocks, making it difficult to perform reliable root-cause analysis using surveys alone
Answer
root causes

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3. Ambiguous: Surveys often fail to reveal the root causes of customer sentiment. In fact, scores can vary based on many outside factors, including geographical bias and industry shocks, making it difficult to perform reliable root-cause analys

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Flashcard 7794002627852

Tags
#abm #agent-based #machine-learning #model #priority #synergistic-integration
Question
As demonstrated by Torrens et al. [9], the individual behavior in an agent-based model can be [...] from samples collected at the individual-agent level.
Answer
machine-learned

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As demonstrated by Torrens et al. [9], the individual behavior in an agent-based model can be machine-learned from samples collected at the individual-agent level.

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