Instance Selection for Classifier Performance Estimation in Meta Learning
نویسندگان
چکیده
منابع مشابه
Instance Selection for Classifier Performance Estimation in Meta Learning
Building an accurate prediction model is challenging and requires appropriate model selection. This process is very time consuming but can be accelerated with meta-learning–automatic model recommendation by estimating the performances of given prediction models without training them. Meta-learning utilizes metadata extracted from the dataset to effectively estimate the accuracy of the model in ...
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Designing an effective criterion for selecting the best rule is a major problem in theprocess of implementing Fuzzy Learning Classifier (FLC) systems. Conventionally confidenceand support or combined measures of these are used as criteria for fuzzy rule evaluation. In thispaper new entities namely precision and recall from the field of Information Retrieval (IR)systems is adapted as alternative...
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The Gamma associative classifier is among the most used classifiers of the alpha-beta associative approach. It had been used successfully to solve many Pattern Recognition tasks, including environmental applications. However, as most classifiers, Gamma suffers with the presence of noisy or mislabeled instances in the training sets. This paper evaluates the impact of using instance selection tec...
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designing an effective criterion for selecting the best rule is a major problem in theprocess of implementing fuzzy learning classifier (flc) systems. conventionally confidenceand support or combined measures of these are used as criteria for fuzzy rule evaluation. in thispaper new entities namely precision and recall from the field of information retrieval (ir)systems is adapted as alternative...
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Pre-processing the dataset is an important stage in the Knowledge Discovery in Datasets (KDD) process. Filtering noise through instance selection is a necessary task. With this, the risk to use misclassified and non-representative instances to train supervised classifiers is reduced. This study aims at improving the performance of the Gamma associative classifier, by introducing a novel similar...
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ژورنال
عنوان ژورنال: Entropy
سال: 2017
ISSN: 1099-4300
DOI: 10.3390/e19110583