Crossword Solver > found answer > LAPELED

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CROSSWORD
ANSWER

lapeled

Searching in Crosswords ...

The answer LAPELED has 1 possible clue(s) in existing crosswords.

Searching in Word Games ...

The word LAPELED is VALID in some board games. Check LAPELED in word games in Scrabble, Words With Friends, see scores, anagrams etc.

Searching in Dictionaries ...

Definitions of lapeled in various dictionaries:

adj - an extension of the collar of a garment [n -S] : LAPELED, LAPELLED

Word Research / Anagrams and more ...

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Possible Crossword Clues
Like most jackets

Last Seen in these Crosswords & Puzzles
Dec 22 2001 New York Times

Lapeled might refer to
Labeled data is a group of samples that have been tagged with one or more labels. Labeling typically takes a set of unlabeled data and augments each piece of that unlabeled data with meaningful tags that are informative. For example, labels might indicate whether a photo contains a horse or a cow, which words were uttered in an audio recording, what type of action is being performed in a video, what the topic of a news article is, what the overall sentiment of a tweet is, whether the dot in an x-ray is a tumor, etc. * Labels can be obtained by asking humans to make judgments about a given piece of unlabeled data (e.g., "Does this photo contain a horse or a cow?"), and are significantly more expensive to obtain than the raw unlabeled data. * After obtaining a labeled dataset, machine learning models can be applied to the data so that new unlabeled data can be presented to the model and a likely label can be guessed or predicted for that piece of unlabeled data.

Lapeled might refer to

Labeled data is a group of samples that have been tagged with one or more labels. Labeling typically takes a set of unlabeled data and augments each piece of that unlabeled data with meaningful tags that are informative. For example, labels might indicate whether a photo contains a horse or a cow, which words were uttered in an audio recording, what type of action is being performed in a video, what the topic of a news article is, what the overall sentiment of a tweet is, whether the dot in an x-ray is a tumor, etc.
* Labels can be obtained by asking humans to make judgments about a given piece of unlabeled data (e.g., "Does this photo contain a horse or a cow?"), and are significantly more expensive to obtain than the raw unlabeled data.
* After obtaining a labeled dataset, machine learning models can be applied to the data so that new unlabeled data can be presented to the model and a likely label can be guessed or predicted for that piece of unlabeled data.

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