Search results
Results from the WOW.Com Content Network
Matplotlib (portmanteau of MATLAB, plot, and library [3]) is a plotting library for the Python programming language and its numerical mathematics extension NumPy.It provides an object-oriented API for embedding plots into applications using general-purpose GUI toolkits like Tkinter, wxPython, Qt, or GTK.
The first prototype was implemented as an interactive, web-based application. [2] UpSet plots are related to Mosaic Plots , although Mosaic plots are designed for categorical instead of set data. UpSet plots became popular as they became available as an R -library based on ggplot2 , [ 3 ] and were subsequently re-implemented in various ...
Using lines of code to compare a 10,000-line project to a 100,000-line project is far more useful than when comparing a 20,000-line project with a 21,000-line project. While it is debatable exactly how to measure lines of code, discrepancies of an order of magnitude can be clear indicators of software complexity or man-hours .
The counting measure can be defined on any measurable space (that is, any set along with a sigma-algebra) but is mostly used on countable sets. [ 1 ] In formal notation, we can turn any set X {\displaystyle X} into a measurable space by taking the power set of X {\displaystyle X} as the sigma-algebra Σ ; {\displaystyle \Sigma ;} that is, all ...
Full width at half maximum. In a distribution, full width at half maximum (FWHM) is the difference between the two values of the independent variable at which the dependent variable is equal to half of its maximum value.
The count–min sketch was invented in 2003 by Graham Cormode and S. Muthu Muthukrishnan [1] and described by them in a 2005 paper. [2] Count–min sketch is an alternative to count sketch and AMS sketch and can be considered an implementation of a counting Bloom filter (Fan et al., 1998 [3]) or multistage-filter. [1]
Figure 1. A 32-segment quadric fractal viewed through "boxes" of different sizes. The pattern illustrates self similarity.. Box counting is a method of gathering data for analyzing complex patterns by breaking a dataset, object, image, etc. into smaller and smaller pieces, typically "box"-shaped, and analyzing the pieces at each smaller scale.
Low-rank matrix approximations are essential tools in the application of kernel methods to large-scale learning problems. [1]Kernel methods (for instance, support vector machines or Gaussian processes [2]) project data points into a high-dimensional or infinite-dimensional feature space and find the optimal splitting hyperplane.