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If ′ =, then for large the set is expected to have the fraction (1 - 1/e) (~63.2%) of the unique samples of , the rest being duplicates. [1] This kind of sample is known as a bootstrap sample. Sampling with replacement ensures each bootstrap is independent from its peers, as it does not depend on previous chosen samples when sampling.
A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]
[1] [4] Sensitivity to model inputs can also be used to judge face validity. [1] For example, if a simulation of a fast food restaurant drive through was run twice with customer arrival rates of 20 per hour and 40 per hour then model outputs such as average wait time or maximum number of customers waiting would be expected to increase with the ...
In statistics and machine learning, the bias–variance tradeoff describes the relationship between a model's complexity, the accuracy of its predictions, and how well it can make predictions on previously unseen data that were not used to train the model. In general, as we increase the number of tunable parameters in a model, it becomes more ...
For the following definitions, two examples will be used. The first is the problem of character recognition given an array of n {\displaystyle n} bits encoding a binary-valued image. The other example is the problem of finding an interval that will correctly classify points within the interval as positive and the points outside of the range as ...
Applying machine learning (ML) (including deep learning) methods to the study of quantum systems is an emergent area of physics research.A basic example of this is quantum state tomography, where a quantum state is learned from measurement. [1]
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A collection of Vietnamese multiple-choice questions for evaluating MRC models. This corpus includes 2,783 Vietnamese multiple-choice questions. 2,783 Question-answer pairs Question Answering/Machine Reading Comprehension 2020 [335] Nguyen et al. Open-Domain Question Answering Goes Conversational via Question Rewriting