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Discuss, Learn and be Happy דיון בשאלות

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Which criteria are related to the interpretability of a model?

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שאלה #131956

		Training time and space complexity.
		Availability of pre-trained models.
done		Model complexity, such as the number of hidden units in a neural network.
		The rate of misclassification errors.

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What does robustness refer to in the context of algorithm preference?

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שאלה #131957

done		The ability of an algorithm to maintain performance under variations in the data or modeling assumptions.
		The complexity of the algorithm's model interpretation.
		The ability of an algorithm to handle missing values in the dataset.
		The ease of tuning the hyperparameters of the algorithm.

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What is incremental learning in the context of algorithm preference?

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שאלה #131958

		The ability of the model to perform well under varying conditions.
		The ease of tuning the model parameters.
done		The ability of the model to learn from new data instances continuously without retraining on the entire dataset.
		The complexity of the model architecture.

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What does it mean for a machine learning algorithm to be "cost-sensitive"?

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שאלה #131959

		It focuses solely on maximizing accuracy without considering the costs of misclassification.
done		It considers the differential costs associated with different types of classification errors when making decisions.
		It prioritizes computational efficiency over model performance.
		It disregards any costs associated with misclassification errors.

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In a medical diagnosis scenario, which classification error may lead to unnecessary medical treatments and potential harm to the patient's health?

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שאלה #131960

done		False positive
		True positive
		True negative
		False negative

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What does "easy embedding" refer to in the context of machine learning algorithms?

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שאלה #131961

		The ease of tuning hyperparameters to optimize model performance.
done		The ease with which a trained model can be incorporated into real-world applications or systems.
		The simplicity of the algorithm's mathematical formulation.
		The interpretability of the model's predictions.

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In the context of algorithm preference, what does "availability" primarily refer to?

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שאלה #131962

		The interpretability of the model's decisions.
		The accuracy of the algorithm's predictions.
		The computational complexity of the algorithm.
done		The accessibility and readiness of the algorithm for use in practical applications.

נערך לפני 6 חודשים Shachar Adam

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In machine learning, what does "multi-class" classification refer to?

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שאלה #131963

done		A classification task where the data instances belong to more than two distinct classes or categories.
		A classification task where the goal is to predict multiple binary outcomes simultaneously.
		A classification task where the goal is to predict the probability of an event occurring.
		A classification task where the algorithm predicts the continuous values of the target variable.

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What is the purpose of K-Fold Cross Validation?

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שאלה #131964

		To train the model on a single fold of the data.
		To ensure the model is trained on all data instances simultaneously.
mood		To average performance scores from multiple folds to obtain a final score.

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What is NOT a typical ratio for splitting data into training and test sets?

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שאלה #131965

done		60:40
		70:30
		80:20
		90:10

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