Docker Desktop. The preferred choice for millions of developers that are building containerized apps. Docker Desktop is a tool for MacOS and Windows machines for the building and sharing of containerized applications and microservices. Access Docker Desktop and follow the guided onboarding to build your first containerized application in minutes.
Arguments xnumeric matrix or data frame, of dimension (ntimes p),say. Dissimilarities will be computedbetween the rows of x. Columns of mode numeric(i.e. All columns when x is a matrix) will be recognized asinterval scaled variables, columns of class factor will berecognized as nominal variables, and columns of class orderedwill be recognized as ordinal variables. Other variable typesshould be specified with the type argument.
Missing values( s) are allowed. Metriccharacter string specifying the metric to be used.The currently available options are 'euclidean' (the default),'manhattan' and 'gower'.Euclidean distances are root sum-of-squares of differences, andmanhattan distances are the sum of absolute differences.“Gower's distance” is chosen by metric 'gower'or automatically if some columns of x are not numeric. Alsoknown as Gower's coefficient (1971),expressed as a dissimilarity, this implies that a particularstandardisation will be applied to each variable, and the“distance” between two units is the sum of all thevariable-specific distances, see the details section. Standlogical flag: if TRUE, then the measurements in xare standardized before calculating thedissimilarities.
Measurements are standardized for each variable(column), by subtracting the variable's mean value and dividing bythe variable's mean absolute deviation.If not all columns of x are numeric, stand willbe ignored and Gower's standardization (based on the) will be applied in any case, see argumentmetric, above, and the details section. Typelist for specifying some (or all) of the types of thevariables (columns) in x. The list may contain the followingcomponents: 'ordratio' (ratio scaled variables to be treated asordinal variables), 'logratio' (ratio scaled variables thatmust be logarithmically transformed), 'asymm' (asymmetricbinary) and 'symm' (symmetric binary variables). Eachcomponent's value is a vector, containing the names or the numbersof the corresponding columns of x.Variables not mentioned in the type list are interpreted asusual (see argument x). Weightsan optional numeric vector of length (p)(= ncol(x)); tobe used in “case 2” (mixed variables, or metric = 'gower'),specifying a weight for each variable ( x,k) instead of(1) in Gower's original formula. WarnBin, warnAsym, warnConstlogicals indicating if thecorresponding type checking warnings should be signalled (when found).
WarnTypelogical indicating if all the type checkingwarnings should be active or not.
PerformanceEach algorithm is implemented using Python and C/C language, if your platform is not supported then Pythonimplementation is used, otherwise C/C. Implementation can be chosen by ccore flag (by default it is always‘True’ and it means that C/C is used), for example: # As by default - C/C part of the library is used xmeansinstance1 = xmeans ( datapoints, startcenters, 20, ccore = True ); # The same - C/C part of the library is used by default xmeansinstance2 = xmeans ( datapoints, startcenters, 20 ); # Switch off core - Python is used xmeansinstance3 = xmeans ( datapoints, startcenters, 20, ccore = False ).
Comments are closed.
|
AuthorWrite something about yourself. No need to be fancy, just an overview. Archives
January 2023
Categories |