Artificial Intelligence |
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7 : An Example of the Concept Car set of possible descriptions and evolving that
set as new examples and near misses are presented . As in the previous section ,
we need some sort of representation language for examples so that we can ...
7 : An Example of the Concept Car set of possible descriptions and evolving that
set as new examples and near misses are presented . As in the previous section ,
we need some sort of representation language for examples so that we can ...
Página 471
For example , testing the attribute color is useless if the color of a car does not
help us to classify it correctly . Ideally , an attribute will separate training instances
into subsets whose members share a common label ( e . g . , positive or negative
) ...
For example , testing the attribute color is useless if the color of a car does not
help us to classify it correctly . Ideally , an attribute will separate training instances
into subsets whose members share a common label ( e . g . , positive or negative
) ...
Página 472
An EBL system attempts to learn from a single example x by explaining why x is
an example of the target concept . The explanation is then generalized , and the
system ' s performance is improved through the availability of this knowledge .
An EBL system attempts to learn from a single example x by explaining why x is
an example of the target concept . The explanation is then generalized , and the
system ' s performance is improved through the availability of this knowledge .
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Contenido
Problems Problem Spaces and Search | 29 |
7 | 61 |
Knowledge Representation Issues | 105 |
Derechos de autor | |
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Términos y frases comunes
active addition agents algorithm allow answer apply approach assertions becomes belief build called Chapter choose clauses combined complete concept consider consistent constraints contains corresponding define dependency described discussed domain elements example fact Figure function given goal heuristic important initial input instance interpretation John kinds knowledge knowledge base labeled language learning logic look match meaning methods move natural necessary node object occur operators output particular path perform position possible predicate present problem procedure produce properties question reasoning relation represent representation result robot rules semantic sentence shown in Figure shows simple single situation slot solution solve space specific statements step stored structure Suppose task techniques things tree true understanding units usually variables weights