Examples of using Data points in English and their translations into Russian
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Official
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Colloquial
containing the data points themselves.
I need more data points to track how the virus is continuing to replicate within the culture medium.
The corresponding procedure will no longer be truly online and instead involve storing all the data points, but is still faster than the brute force method.
Formally, given a set of data points x, the k centers ci are to be chosen
we place a normal kernel with variance 2.25(indicated by the red dashed lines) on each of the data points xi.
The monitoring network has grown to over 3,100 stations with over 4 million data points.
Figure 1a below provides an illustration of the previous output table in which there were no data points for Turkmenistan and Uzbekistan.
Finally, researchers agree to immediately inform CDER if they have inadvertently accessed individual data points.
NativeTrack analyses multiple data points including the device profile,
The 28-day data were selected for further analysis because there were more data points and the shorter time interval provided greater resolution for studying the effects of level II factors.
Furthermore, most of BIRCH's predecessors inspect all data points(or all currently existing clusters) equally for each'clustering decision'
TOO FEW ENTRIES The linearization table has too few data points S Carry out linearization at at least 5 points(HART communication
represents a measure of the similarity between data points with indices i{\displaystyle i}
The BIRCH algorithm takes as input a set of N data points, represented as real-valued vectors,
target variable, play, and 14 data points.
length of each iteration and number of available data points at attack time.
for modeling this theory, but it currently requires too many observational data points to be computationally feasible, and not enough such data points are available to cosmologists yet.
in two graphic modes: relation between line energy and position(Show data points mode) and its nonlinearity graphic(Show nonlinearity mode),
Jörg Sander in 2000 for finding anomalous data points by measuring the local deviation of a given data point with respect to its neighbours.
Its inventors claim BIRCH to be the"first clustering algorithm proposed in the database area to handle'noise'(data points that are not part of the underlying pattern) effectively", beating DBSCAN by two months.