منابع مشابه
IRDDS: Instance reduction based on Distance-based decision surface
In instance-based learning, a training set is given to a classifier for classifying new instances. In practice, not all information in the training set is useful for classifiers. Therefore, it is convenient to discard irrelevant instances from the training set. This process is known as instance reduction, which is an important task for classifiers since through this process the time for classif...
متن کاملEvidence based medicine manifesto for better healthcare.
120 Informed decision-making requires clinicians and patients to identify and integrate relevant evidence. But with the questionable integrity of much of today’s evidence, the lack of research answering questions that matter to patients and the lack of evidence to inform shared decision-making how are they expected to do this? Too many research studies are poorly designed or executed. Too much ...
متن کاملMultiresolution Instance-Based Learning
Instance-based learning methods explicitly remem ber all the data that they receive They usually have no training phase and only at prediction time do they perform computation Then they take a query search the database for similar datapoints and build an on-line local model (such as a local average or local regression) with which to predict an output value In this paper we review the advantage...
متن کاملCompositional Instance-Based Learning
This paper proposes a new algorithm for acquisition of preference predicates by a learning apprentice, termed Compositional Instance-Based Learning (CIBL), that permits multiple instances of a preference predicate to be composed, directly exploiting the transitivity of preference predicates. In an empirical evaluation, CIBL was consistently more accurate than a I-NN instance-based learning stra...
متن کاملPrababilistic Instance-Based Learning
Traditional instance-based learning methods base their predictions directly on (training) data that has been stored in the memory. The predictions are based on weighting the contributions of the individual stored instances by a distance function implementing a domain-dependent similarity metrics. This basic approach suuers from three drawbacks: com-putationally expensive prediction when the dat...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Behavioral and Brain Sciences
سال: 2000
ISSN: 0140-525X,1469-1825
DOI: 10.1017/s0140525x00383352