File: C:/Program Files/R/R-4.4.0/library/cluster/po/en@quot/LC_MESSAGES/R-cluster.mo
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Z ( E O ` K 4 # V & X J ) : a D . 3 P > ? " $ - C F 8 ' M %d observation (%s) has *only* NAs --> omit them for clustering! %d observations (%s ...) have *only* NAs --> omit them for clustering! %s has constant columns %s; these are standardized to 0 %s has invalid column names %s must be in 1:ncol(x) %s must contain column names or numbers 'A' must be p x p cov-matrix defining an ellipsoid 'B' has to be a positive integer 'col.clus' should have length 4 when color is TRUE 'dmatrix' is not a dissimilarity matrix compatible to 'x' 'full' must be FALSE, TRUE, or a number in [0, 1] 'iniMem.p' must be a nonnegative n * k matrix with rowSums == 1 'k' (number of clusters) must be in {1,2, .., n/2 -1} 'm', a membership matrix, must be nonnegative with rowSums == 1 'maxit' must be non-negative integer 'medoids' must be NULL or vector of %d distinct indices in {1,2, .., n}, n=%d 'memb.exp' must be a finite number > 1 'n' must be >= 2 'par.method' must be of length 1, 3, or 4 'samples' should be at least 1 'sampsize' = %d should not be larger than the number of objects, %d 'sampsize' should be at least %d = max(2, 1+ number of clusters) 'weights' must be of length p (or 1) 'x' is a "dist" object, but should be a data matrix or frame 'x' is not and cannot be converted to class "dissimilarity" 'x' must be numeric n x p matrix 'x' must only have integer codes >>>>> funny case in clusplot.default() -- please report! All variables must be binary (e.g., a factor with 2 levels, both present). Cannot keep data when 'x' is a dissimilarity! Distance computations with NAs: using correct instead of pre-2016 wrong formula.
Use 'correct.d=FALSE' to get previous results or set 'correct.d=TRUE' explicitly
to suppress this warning. Distances must be result of dist or a square matrix. Each of the random samples contains objects between which no distance can be computed. Error in C routine for the spanning ellipsoid,
rank problem?? FANNY algorithm has not converged in 'maxit' = %d iterations For each of the %d samples, at least one object was found which could not be assigned to a cluster (because of missing values). Missing values were displaced by the median of the corresponding variable(s) NA values in the dissimilarity matrix not allowed. NA-values are not allowed in clustering vector NA-values are not allowed in dist-like 'x'. NA-values in the dissimilarity matrix not allowed. Need either a dissimilarity 'dist' or diss.matrix 'dmatrix' No clustering performed, NA's in dissimilarity matrix. No clustering performed, NA-values in the dissimilarity matrix. No clustering performed, NAs in the computed dissimilarity matrix. No clustering performed, a variable was found with all non missing values identical. No clustering performed, all variables have at least one missing value. No clustering performed, an object was found with all values missing. No clustering performed, found variable with more than half values missing. No valid silhouette information (#{clusters} =? 1) Number of clusters 'k' must be in {1,2, .., n-1}; hence n >= 2 Observation %s has *only* NAs --> omit it for clustering Observations %s have *only* NAs --> omit them for clustering! Set either 'variant' or 'pamonce', but not both The clustering vector is of incorrect length The number of cluster should be at least 1 and at most n-1. algorithm possibly not converged in %d iterations ambiguous clustering method at least one binary variable has more than 2 levels. at least one binary variable has not 2 different levels. at least one binary variable has values not in {0,1,NA} binary variable(s) %s treated as interval scaled clustering 'x' and dissimilarity 'dist' are incompatible computed some negative or all 0 probabilities ellipsoidPoints() not yet implemented for p >= 3 dim. error from .C(cl_pam, *): invalid medID's full silhouette is only available for results of 'clara(*, keep.data = TRUE)' have %d observations, but not more than %d are allowed index has to be a function or a list of function invalid %s; must be named list invalid 'correct.d' invalid 'jstop' from .C(cl_clara,.): invalid 'silhouette' object invalid 'spaceH0': invalid 'twins' object invalid clustering method invalid partition object invalid silhouette structure invalid type %s for column numbers %s mona() needs at least p >= 2 variables (in current implementation) need at least 2 objects to cluster no diss nor data found for clusplot()' no diss nor data found, nor the original argument of %s no points without missing values omitting NAs one or more objects contain only missing values one or more variables contain only missing values setting 'logical' variable %s to type 'asymm' setting 'logical' variables %s to type 'asymm' specified both 'full' and 'subset'; will use 'subset' the memberships are all very close to 1/k. Maybe decrease 'memb.exp' ? the square matrix is not symmetric. when 'medoids.x' is FALSE, 'keep.data' must be too with mixed variables, metric "gower" is used automatically x is not a data matrix x is not a dataframe or a numeric matrix. x is not a numeric dataframe or matrix. x is not numeric x must be a matrix or data frame. Project-Id-Version: cluster 2.1.3
PO-Revision-Date: 2021-08-19 20:27
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%d observation (%s) has *only* NAs --> omit them for clustering! %d observations (%s ...) have *only* NAs --> omit them for clustering! %s has constant columns %s; these are standardized to 0 %s has invalid column names %s must be in 1:ncol(x) %s must contain column names or numbers ‘A’ must be p x p cov-matrix defining an ellipsoid ‘B’ has to be a positive integer ‘col.clus’ should have length 4 when color is TRUE ‘dmatrix’ is not a dissimilarity matrix compatible to ‘x’ ‘full’ must be FALSE, TRUE, or a number in [0, 1] ‘iniMem.p’ must be a nonnegative n * k matrix with rowSums == 1 ‘k’ (number of clusters) must be in {1,2, .., n/2 -1} ‘m’, a membership matrix, must be nonnegative with rowSums == 1 ‘maxit’ must be non-negative integer ‘medoids’ must be NULL or vector of %d distinct indices in {1,2, .., n}, n=%d ‘memb.exp’ must be a finite number > 1 ‘n’ must be >= 2 ‘par.method’ must be of length 1, 3, or 4 ‘samples’ should be at least 1 ‘sampsize’ = %d should not be larger than the number of objects, %d ‘sampsize’ should be at least %d = max(2, 1+ number of clusters) ‘weights’ must be of length p (or 1) ‘x’ is a "dist" object, but should be a data matrix or frame ‘x’ is not and cannot be converted to class "dissimilarity" ‘x’ must be numeric n x p matrix ‘x’ must only have integer codes >>>>> funny case in clusplot.default() -- please report! All variables must be binary (e.g., a factor with 2 levels, both present). Cannot keep data when ‘x’ is a dissimilarity! Distance computations with NAs: using correct instead of pre-2016 wrong formula.
Use ‘correct.d=FALSE’ to get previous results or set ‘correct.d=TRUE’ explicitly
to suppress this warning. Distances must be result of dist or a square matrix. Each of the random samples contains objects between which no distance can be computed. Error in C routine for the spanning ellipsoid,
rank problem?? FANNY algorithm has not converged in ‘maxit’ = %d iterations For each of the %d samples, at least one object was found which could not be assigned to a cluster (because of missing values). Missing values were displaced by the median of the corresponding variable(s) NA values in the dissimilarity matrix not allowed. NA-values are not allowed in clustering vector NA-values are not allowed in dist-like ‘x’. NA-values in the dissimilarity matrix not allowed. Need either a dissimilarity ‘dist’ or diss.matrix ‘dmatrix’ No clustering performed, NA's in dissimilarity matrix. No clustering performed, NA-values in the dissimilarity matrix. No clustering performed, NAs in the computed dissimilarity matrix. No clustering performed, a variable was found with all non missing values identical. No clustering performed, all variables have at least one missing value. No clustering performed, an object was found with all values missing. No clustering performed, found variable with more than half values missing. No valid silhouette information (#{clusters} =? 1) Number of clusters ‘k’ must be in {1,2, .., n-1}; hence n >= 2 Observation %s has *only* NAs --> omit it for clustering Observations %s have *only* NAs --> omit them for clustering! Set either ‘variant’ or ‘pamonce’, but not both The clustering vector is of incorrect length The number of cluster should be at least 1 and at most n-1. algorithm possibly not converged in %d iterations ambiguous clustering method at least one binary variable has more than 2 levels. at least one binary variable has not 2 different levels. at least one binary variable has values not in {0,1,NA} binary variable(s) %s treated as interval scaled clustering ‘x’ and dissimilarity ‘dist’ are incompatible computed some negative or all 0 probabilities ellipsoidPoints() not yet implemented for p >= 3 dim. error from .C(cl_pam, *): invalid medID's full silhouette is only available for results of ‘clara(*, keep.data = TRUE)’ have %d observations, but not more than %d are allowed index has to be a function or a list of function invalid %s; must be named list invalid ‘correct.d’ invalid ‘jstop’ from .C(cl_clara,.): invalid ‘silhouette’ object invalid ‘spaceH0’: invalid ‘twins’ object invalid clustering method invalid partition object invalid silhouette structure invalid type %s for column numbers %s mona() needs at least p >= 2 variables (in current implementation) need at least 2 objects to cluster no diss nor data found for clusplot()' no diss nor data found, nor the original argument of %s no points without missing values omitting NAs one or more objects contain only missing values one or more variables contain only missing values setting ‘logical’ variable %s to type ‘asymm’ setting ‘logical’ variables %s to type ‘asymm’ specified both ‘full’ and ‘subset’; will use ‘subset’ the memberships are all very close to 1/k. Maybe decrease ‘memb.exp’ ? the square matrix is not symmetric. when ‘medoids.x’ is FALSE, ‘keep.data’ must be too with mixed variables, metric "gower" is used automatically x is not a data matrix x is not a dataframe or a numeric matrix. x is not a numeric dataframe or matrix. x is not numeric x must be a matrix or data frame.