### Some articles on *points, data points, data, point, data point*:

Geometric Hashing

... efficiently finding two-dimensional objects represented by discrete

... efficiently finding two-dimensional objects represented by discrete

**points**that have undergone an affine transformation, though extensions exist to some other ... In an off-line step, the objects are encoded by treating each pairs of**points**as a geometric basis ... The remaining**points**can be represented in an invariant fashion with respect to this basis using two parameters ...The Nethernet - Game Experience

... through features of the HUD and through increased web browsing, players lose or gain

... through features of the HUD and through increased web browsing, players lose or gain

**data points**...**Data points**allow users to buy different types of tools which can enhance the previously mentioned features of the HUD ... In addition, accumulated**data points**allow users to select a character type ...Least Absolute Deviations - Other Properties

... In the case of a set of (x,y)

... In the case of a set of (x,y)

**data**, the least absolute deviations line will always pass through at least two of the**data points**, unless there are multiple solutions ... least two lines, each of which passes through at least two**data points**... surface will pass through k of the**data points**...Locality-sensitive Hashing - LSH Algorithm For Nearest Neighbor Search

... In the preprocessing step we hash all

... In the preprocessing step we hash all

**points**from the**data**set into each of the hash tables ... Given a query**point**, the algorithm iterates over the hash functions ... For each considered, it retrieves the**data points**that are hashed into the same bucket as ...BIRCH (data Clustering) - BIRCH Clustering Algorithm

... Given a set of N d-dimensional

... Given a set of N d-dimensional

**data points**, the clustering feature of the set is defined as the triple, where is the linear sum and is the square sum ... of the dataset because each entry in a leaf node is not a single**data point**but a subcluster ... the algorithm in the first step it scans all**data**and builds an initial memory CF tree using the given amount of memory ...### Famous quotes containing the words points and/or data:

“The dominant metaphor of conceptual relativism, that of differing *points* of view, seems to betray an underlying paradox. Different *points* of view make sense, but only if there is a common co-ordinate system on which to plot them; yet the existence of a common system belies the claim of dramatic incomparability.”

—Donald Davidson (b. 1917)

“Mental health *data* from the 1950’s on middle-aged women showed them to be a particularly distressed group, vulnerable to depression and feelings of uselessness. This isn’t surprising. If society tells you that your main role is to be attractive to men and you are getting crow’s feet, and to be a mother to children and yours are leaving home, no wonder you are distressed.”

—Grace Baruch (20th century)

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