Search results
Results from the WOW.Com Content Network
COMMAND.COM, the original Microsoft command line processor introduced on MS-DOS as well as Windows 9x, in 32-bit versions of NT-based Windows via NTVDM; cmd.exe, successor of COMMAND.COM introduced on OS/2 and Windows NT systems, although COMMAND.COM is still available in virtual DOS machines on IA-32 versions of those operating systems also.
An MS-DOS command line, illustrating parsing into command and arguments. A command-line argument or parameter is an item of information provided to a program when it is started. [23] A program can have many command-line arguments that identify sources or destinations of information, or that alter the operation of the program.
Lasso includes a simple template system allowing code to control generation of HTML and other content types. Lasso is an object-oriented programming language in which every value is an object. It also supports procedural programming through unbound methods. The language uses traits and multiple dispatch extensively.
In statistics, the graphical lasso [1] is a sparse penalized maximum likelihood estimator for the concentration or precision matrix (inverse of covariance matrix) of a multivariate elliptical distribution.
BAC – an executable image for the RSTS/E system, created using the BASIC-PLUS COMPILE command [17] BPL – a Win32 PE file created with Delphi or C++Builder containing a package. Bundle – a Macintosh plugin created with Xcode or make which holds executable code, data files, and folders for that code.
Process Lasso is Windows process automation and optimization software developed by Jeremy Collake of Bitsum Technologies. It features a graphical user interface that allows for automating various process-related tasks, and several novel algorithms to control how processes are run.
It is easily modified to produce efficient algorithms for other methods producing similar results, like the lasso and forward stagewise regression. It is effective in contexts where p ≫ n (i.e., when the number of predictors p is significantly greater than the number of points n) [2] The disadvantages of the LARS method include:
The result of fitting a set of data points with a quadratic function Conic fitting a set of points using least-squares approximation. In regression analysis, least squares is a parameter estimation method based on minimizing the sum of the squares of the residuals (a residual being the difference between an observed value and the fitted value provided by a model) made in the results of each ...