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CROSSWORD
ANSWER

determining

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The answer DETERMINING has 5 possible clue(s) in existing crosswords.

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

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Definitions of determining in various dictionaries:

verb - establish after a calculation, investigation, experiment, survey, or study

verb - shape or influence

verb - fix conclusively or authoritatively

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Possible Crossword Clues
finding out definitively
Resolving to prevent deployment of explosives in the main?
Making a decision to discourage a dying industry
Firmly deciding

Last Seen in these Crosswords & Puzzles
Jul 21 2016 The Times - Cryptic
Dec 29 2015 7 Little Words Daily Puzzle
Dec 29 2015 7 Little Words Daily Puzzle
May 19 2007 The Times - Concise
Mar 24 2007 The Times - Cryptic

Possible Dictionary Clues
Present participle of determine.
causing something to occur or be done in a particular way serving to decide something.
Causing something to occur or be done in a particular way serving to decide something.

Determining description
Determining the number of clusters in a data set, a quantity often labelled k as in the k-means algorithm, is a frequent problem in data clustering, and is a distinct issue from the process of actually solving the clustering problem. * For a certain class of clustering algorithms (in particular k-means, k-medoids and expectation–maximization algorithm), there is a parameter commonly referred to as k that specifies the number of clusters to detect. Other algorithms such as DBSCAN and OPTICS algorithm do not require the specification of this parameter; hierarchical clustering avoids the problem altogether. * The correct choice of k is often ambiguous, with interpretations depending on the shape and scale of the distribution of points in a data set and the desired clustering resolution of the user. In addition, increasing k without penalty will always reduce the amount of error in the resulting clustering, to the extreme case of zero error if each data point is considered its own cluster (i.e., when k equals the number of data points, n). Intuitively then, the optimal choice of k will strike a balance between maximum compression of the data using a single cluster, and maximum accuracy by assigning each data point to its own cluster. If an appropriate value of k is not apparent from prior knowledge of the properties of the data set, it must be chosen somehow. There are several categories of methods for making this decision.

Determining description

Determining the number of clusters in a data set, a quantity often labelled k as in the k-means algorithm, is a frequent problem in data clustering, and is a distinct issue from the process of actually solving the clustering problem.
* For a certain class of clustering algorithms (in particular k-means, k-medoids and expectation–maximization algorithm), there is a parameter commonly referred to as k that specifies the number of clusters to detect. Other algorithms such as DBSCAN and OPTICS algorithm do not require the specification of this parameter; hierarchical clustering avoids the problem altogether.
* The correct choice of k is often ambiguous, with interpretations depending on the shape and scale of the distribution of points in a data set and the desired clustering resolution of the user. In addition, increasing k without penalty will always reduce the amount of error in the resulting clustering, to the extreme case of zero error if each data point is considered its own cluster (i.e., when k equals the number of data points, n). Intuitively then, the optimal choice of k will strike a balance between maximum compression of the data using a single cluster, and maximum accuracy by assigning each data point to its own cluster. If an appropriate value of k is not apparent from prior knowledge of the properties of the data set, it must be chosen somehow. There are several categories of methods for making this decision.

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