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Classification with automatic selection of promising learning data
Classification with automatic selection of promising learning data
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机译：自动选择有希望的学习数据进行分类
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摘要
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摘要
Device (1) for classifying at least one input variable value (11), comprising: • a plurality of individual evaluators (12a-12c) trainable by means of learning input quantity values (11a) and learning output values (13c), which are pre-trained on identical sets of learning input values (11a) and which are respectively adapted to the input quantity value (11 ) assign a probability distribution (P a , P b , P c ), this probability distribution (P a , P b , P c ) to each of the discrete classes (13a), or to each possible value of the classification size (13b), indicates with which probability the input variable value (11) is to be mapped to the respective class (13a) or to the respective value (13b); and A confidence module (14), which is designed to determine the uncertainty (15) from the deviations between the probability distributions (P a , P b , P c ) supplied by the individual evaluators (12a-12c), with which the classification is afflicted wherein the device (1) additionally comprises a feedback module (16) adapted to respond to this input variable value (11) as an answer in response to the uncertainty (15) for an input value (11) satisfying a predetermined criterion (15a) Feedback input value (11a) to all individual assessors (12a-12c), and / or to control a perceptible by the user (18) of the device (1) physical warning device (17).
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机译：用于对至少一个输入变量值（11）进行分类的设备（1），包括：•可通过学习输入量值（11a）和学习输出值（13c）进行训练的多个独立评估器（12a-12c），在相同的一组学习输入值（11a）上进行了预训练，并且分别适应了输入量值（11），分配了概率分布（P a ，P b ，P c ），该概率分布（P a ，P b ，P c ）到每个离散类别（13a）或分类大小（13b）的每个可能值表示以何种概率将输入变量值（11）映射到各个类别（13a）或各个值（13b）;和置信度模块（14），用于根据概率分布（P a ，P b ，P 由各个评估器（12a-12c）提供的c ），因此难以进行分类，其中设备（1）还包括一个反馈模块（16），该模块响应于该输入变量值（11）响应不确定性（15）的答案，输入值（11）满足预定标准（15a）将输入值（11a）反馈给所有单独的评估者（12a-12c），和/或控制用户的可感知性（ 18）设备（1）物理警告设备（17）。
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