From 262d654e6f9a383a9200ea7a78a0cccbfc75e624 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Gabija=20Vaitkevi=C4=8Di=C5=ABt=C4=97?= Date: Wed, 1 Oct 2025 13:32:50 +0200 Subject: [PATCH 1/2] Added translation using Weblate (Lithuanian) --- po/R-lt.po | 1286 ++++++++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 1286 insertions(+) create mode 100644 po/R-lt.po diff --git a/po/R-lt.po b/po/R-lt.po new file mode 100644 index 00000000..7aa6e92e --- /dev/null +++ b/po/R-lt.po @@ -0,0 +1,1286 @@ +msgid "" +msgstr "" +"Project-Id-Version: jaspMachineLearning 0.95.0\n" +"POT-Creation-Date: 2025-06-28 03:36\n" +"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" +"Last-Translator: Automatically generated\n" +"Language-Team: none\n" +"Language: lt\n" +"MIME-Version: 1.0\n" +"Content-Type: text/plain; charset=UTF-8\n" +"Content-Transfer-Encoding: 8bit\n" +"Plural-Forms: nplurals=3; plural=(n % 10 == 1 && (n % 100 < 11 || n % 100 > " +"19)) ? 0 : ((n % 10 >= 2 && n % 10 <= 9 && (n % 100 < 11 || n % 100 > 19)) ? " +"1 : 2);\n" + +msgid "An error occurred in the analysis: %s" +msgstr "" + +msgid "K-Nearest Neighbors Classification" +msgstr "" + +msgid "Linear Discriminant Classification" +msgstr "" + +msgid "Random Forest Classification" +msgstr "" + +msgid "Boosting Classification" +msgstr "" + +msgid "Neural Network Classification" +msgstr "" + +msgid "Decision Tree Classification" +msgstr "" + +msgid "Support Vector Machine Classification" +msgstr "" + +msgid "Naive Bayes Classification" +msgstr "" + +msgid "Logistic / Multinomial Regression Classification" +msgstr "" + +msgid "Model Summary: %1$s" +msgstr "" + +msgid "Nearest neighbors" +msgstr "" + +msgid "Weights" +msgstr "" + +msgid "Distance" +msgstr "" + +msgid "Linear Discriminants" +msgstr "" + +msgid "Method" +msgstr "" + +msgid "Trees" +msgstr "" + +msgid "Features per split" +msgstr "" + +msgid "Shrinkage" +msgstr "" + +msgid "Hidden Layers" +msgstr "" + +msgid "Nodes" +msgstr "" + +msgid "Complexity penalty" +msgstr "" + +msgid "Splits" +msgstr "" + +msgid "Violation cost" +msgstr "" + +msgid "Support Vectors" +msgstr "" + +msgid "Smoothing" +msgstr "" + +msgid "Family" +msgstr "" + +msgid "Link" +msgstr "" + +msgid "n(Train)" +msgstr "" + +msgid "n(Validation)" +msgstr "" + +msgid "n(Test)" +msgstr "" + +msgid "Validation Accuracy" +msgstr "" + +msgid "Test Accuracy" +msgstr "" + +msgid "OOB Accuracy" +msgstr "" + +msgid "Please provide a target variable and at least %i feature variable(s)." +msgstr "" + +msgid "The trained model is saved as %1$s." +msgstr "" + +msgid "The trained model is not saved because the some of the variable names in the model contain spaces (i.e., ' ') or underscores (i.e., '_'). Please remove all such characters from the variable names and try saving the model again." +msgstr "" + +msgid "The trained model is not saved until a file name is specified under 'Save as'." +msgstr "" + +msgid "The model is optimized with respect to the validation set accuracy." +msgstr "" + +msgid "The optimum number of nearest neighbors is the maximum number. You might want to adjust the range of optimization." +msgstr "" + +msgid "Manhattan" +msgstr "" + +msgid "Euclidean" +msgstr "" + +msgid "Moment" +msgstr "" + +msgid "MLE" +msgstr "" + +msgid "MVE" +msgstr "" + +msgid "t" +msgstr "" + +msgid "The model is optimized with respect to the out-of-bag accuracy." +msgstr "" + +msgid "The model is optimized with respect to the sum of squares." +msgstr "" + +msgid "Model Summary: Logistic Regression Classification" +msgstr "" + +msgid "Model Summary: Multinomial Regression Classification" +msgstr "" + +msgid "Confusion Matrix" +msgstr "" + +msgid "Observed" +msgstr "" + +msgid "Predicted" +msgstr "" + +msgid "Decision Boundary Matrix" +msgstr "" + +msgid "Cannot create plot: You need at least two (numeric) features to create the decision boundary matrix. You have currently included only one feature." +msgstr "" + +msgid "Cannot create matrix: not enough numeric variables remain after removing factor variables. You need at least 2 numeric variables." +msgstr "" + +msgid "ROC Curves Plot" +msgstr "" + +msgid "False Positive Rate" +msgstr "" + +msgid "True Positive Rate" +msgstr "" + +msgid "Perfect separation" +msgstr "" + +msgid "Andrews Curves Plot" +msgstr "" + +msgid "Andrews curves require a minimum of 2 feature variables." +msgstr "" + +msgid "Box's M-test for Homogeneity of Covariance Matrices" +msgstr "" + +msgid "Model Performance Metrics" +msgstr "" + +msgid "Support" +msgstr "" + +msgid "Accuracy" +msgstr "" + +msgid "Precision (Positive Predictive Value)" +msgstr "" + +msgid "Recall (True Positive Rate)" +msgstr "" + +msgid "False Discovery Rate" +msgstr "" + +msgid "F1 Score" +msgstr "" + +msgid "Matthews Correlation Coefficient" +msgstr "" + +msgid "Area Under Curve (AUC)" +msgstr "" + +msgid "Negative Predictive Value" +msgstr "" + +msgid "True Negative Rate" +msgstr "" + +msgid "False Negative Rate" +msgstr "" + +msgid "False Omission Rate" +msgstr "" + +msgid "Threat Score" +msgstr "" + +msgid "Statistical Parity" +msgstr "" + +msgid "All metrics are calculated for every class against all other classes." +msgstr "" + +msgid "Average / Total" +msgstr "" + +msgid "Class Proportions" +msgstr "" + +msgid "Data Set" +msgstr "" + +msgid "Training Set" +msgstr "" + +msgid "Validation Set" +msgstr "" + +msgid "Training and Validation Set" +msgstr "" + +msgid "Test Set" +msgstr "" + +msgid "You have specified more clusters than distinct data points. Please choose a number lower than %s." +msgstr "" + +msgid "R package error: The hclust clustering algorithm from the stats R package cannot handle data that has 65536 or more rows. We are working on a solution for this problem. Please try another algorithm in the meantime." +msgstr "" + +msgid "K-Means Clustering" +msgstr "" + +msgid "K-Medians Clustering" +msgstr "" + +msgid "K-Medoids Clustering" +msgstr "" + +msgid "Fuzzy C-Means Clustering" +msgstr "" + +msgid "Hierarchical Clustering" +msgstr "" + +msgid "Density-Based Clustering" +msgstr "" + +msgid "Random Forest Clustering" +msgstr "" + +msgid "Model-Based Clustering" +msgstr "" + +msgid "Clusters" +msgstr "" + +msgid "N" +msgstr "" + +msgid "R%s" +msgstr "" + +msgid "AIC" +msgstr "" + +msgid "BIC" +msgstr "" + +msgid "Silhouette" +msgstr "" + +msgid "Please provide at least 2 features." +msgstr "" + +msgid "silhouette" +msgstr "" + +msgid "The model is optimized with respect to the %s value." +msgstr "" + +msgid "The optimum number of clusters is the maximum number of clusters. You might want to adjust the range of optimization." +msgstr "" + +msgid "The model contains 0 clusters and only Noisepoints, we advise to change 'Epsilon neighborhood size' and 'Min. core points' parameters under 'Training parameters'." +msgstr "" + +msgid "The model contains 1 cluster and no Noisepoints. You may want to change 'Epsilon neighborhood size' and 'Min. core points' parameters under 'Training parameters'." +msgstr "" + +msgid "spherical with equal volume" +msgstr "" + +msgid "spherical with unequal volume" +msgstr "" + +msgid "diagonal with equal volume and shape" +msgstr "" + +msgid "diagonal with varying volume and equal shape" +msgstr "" + +msgid "diagonal with equal volume and varying shape" +msgstr "" + +msgid "diagonal with varying volume and shape" +msgstr "" + +msgid "ellipsoidal with equal volume, shape, and orientation" +msgstr "" + +msgid "ellipsoidal with equal shape and orientation" +msgstr "" + +msgid "ellipsoidal with equal volume and orientation" +msgstr "" + +msgid "ellipsoidal with equal orientation" +msgstr "" + +msgid "ellipsoidal with equal volume and equal shape" +msgstr "" + +msgid "ellipsoidal with equal shape" +msgstr "" + +msgid "ellipsoidal with equal volume" +msgstr "" + +msgid "ellipsoidal with varying volume, shape, and orientation" +msgstr "" + +msgid "The model is %1$s." +msgstr "" + +msgid "The features in the model are unstandardized." +msgstr "" + +msgid "Cluster Information" +msgstr "" + +msgid "Cluster" +msgstr "" + +msgid "Size" +msgstr "" + +msgid "Explained proportion within-cluster heterogeneity" +msgstr "" + +msgid "Within sum of squares" +msgstr "" + +msgid "Silhouette score" +msgstr "" + +msgid "Center %s" +msgstr "" + +msgid "Noisepoints" +msgstr "" + +msgid "The Between Sum of Squares of the %1$s cluster model is %2$s" +msgstr "" + +msgid "The Total Sum of Squares of the %1$s cluster model is %2$s" +msgstr "" + +msgid "Value" +msgstr "" + +msgid "Maximum diameter" +msgstr "" + +msgid "Minimum separation" +msgstr "" + +msgid "Pearson's %s" +msgstr "" + +msgid "Dunn index" +msgstr "" + +msgid "Entropy" +msgstr "" + +msgid "Calinski-Harabasz index" +msgstr "" + +msgid "All metrics are based on the euclidean distance." +msgstr "" + +msgid "Evaluation metrics cannot be computed when there is only 1 cluster." +msgstr "" + +msgid "t-SNE Cluster Plot" +msgstr "" + +msgid "Noisepoint" +msgstr "" + +msgid "Elbow Method Plot" +msgstr "" + +msgid "WSS" +msgstr "" + +msgid "Number of Clusters" +msgstr "" + +msgid "Lowest %s" +msgstr "" + +msgid "Cluster Means" +msgstr "" + +msgid "Cluster %s" +msgstr "" + +msgid "Cluster Density Plots" +msgstr "" + +msgid "Density" +msgstr "" + +msgid "Feature" +msgstr "" + +msgid "All Features" +msgstr "" + +msgid "Cluster Mean Plots" +msgstr "" + +msgid "Cluster Mean" +msgstr "" + +msgid "Insufficient RAM available to compute the distance matrix. The analysis tried to allocate %s Gb" +msgstr "" + +msgid "An error occurred in the analysis: %1$s" +msgstr "" + +msgid "Cluster Matrix Plot" +msgstr "" + +msgid "The variable '%s' can't be both a feature and a test set indicator." +msgstr "" + +msgid "Your test set indicator should be binary, containing only 1 (included in test set) and 0 (excluded from test set)." +msgstr "" + +msgid "There is only one observation in each level of the factor %1$s, please remove this factor as a feature." +msgstr "" + +msgid "There is only one observation in each level of the factors %1$s, please remove these factors as a feature." +msgstr "" + +msgid "test set" +msgstr "" + +msgid "validation set" +msgstr "" + +msgid "new dataset" +msgstr "" + +msgid "or use a different test set (e.g., automatically by setting a different seed or manually by specifying the test set indicator)" +msgstr "" + +msgid "or use a different validation set by setting a different seed" +msgstr "" + +msgid "Some factors in the %1$s have levels that do not appear in the training set. Please remove the rows with the following levels from the dataset%2$s.\n\n%3$s" +msgstr "" + +msgid "You have specified more nearest neighbors than there are observations in the training set. Please choose a number lower than %d." +msgstr "" + +msgid "You have specified more folds than there are observations in the training and validation set. Please choose a number lower than %d." +msgstr "" + +msgid "K-Nearest Neighbors Regression" +msgstr "" + +msgid "Regularized Linear Regression" +msgstr "" + +msgid "Random Forest Regression" +msgstr "" + +msgid "Boosting Regression" +msgstr "" + +msgid "Neural Network Regression" +msgstr "" + +msgid "Decision Tree Regression" +msgstr "" + +msgid "Support Vector Machine Regression" +msgstr "" + +msgid "Linear Regression" +msgstr "" + +msgid "Penalty" +msgstr "" + +msgid "Loss function" +msgstr "" + +msgid "Validation MSE" +msgstr "" + +msgid "Test MSE" +msgstr "" + +msgid "OOB Error" +msgstr "" + +msgid "R%1$s" +msgstr "" + +msgid "Adjusted R%1$s" +msgstr "" + +msgid "Please provide a target variable and at least %d feature variable(s)." +msgstr "" + +msgid "The model is optimized with respect to the validation set mean squared error." +msgstr "" + +msgid "When %s is set to 0 linear regression is performed." +msgstr "" + +msgid "The model is optimized with respect to the out-of-bag mean squared error." +msgstr "" + +msgid "Gaussian" +msgstr "" + +msgid "Laplace" +msgstr "" + +msgid "MSE(scaled)" +msgstr "" + +msgid "Values" +msgstr "" + +msgid "R%s cannot be computed due to lack of variance in the predictions." +msgstr "" + +msgid "Predictive Performance Plot" +msgstr "" + +msgid "Observed Test Values" +msgstr "" + +msgid "Predicted Test Values" +msgstr "" + +msgid "Data Split" +msgstr "" + +msgid "Train: %d" +msgstr "" + +msgid "Test: %d" +msgstr "" + +msgid "Total: %d" +msgstr "" + +msgid "Validation: %d" +msgstr "" + +msgid "Train and validation: %d" +msgstr "" + +msgid "Additive Explanations for Predictions of New Cases" +msgstr "" + +msgid "Additive Explanations for Predictions of Test Set Cases" +msgstr "" + +msgid "Case" +msgstr "" + +msgid "Predicted (Prob.)" +msgstr "" + +msgid "Base" +msgstr "" + +msgid "An error occurred when computing the results for this table: %1$s" +msgstr "" + +msgid "Displayed values represent feature contributions to the predicted value without features (column 'Base') for the test set." +msgstr "" + +msgid "Displayed values represent feature contributions to the predicted class probability without features (column 'Base') for the test set." +msgstr "" + +msgid "Feature Importance Metrics" +msgstr "" + +msgid "Mean dropout loss" +msgstr "" + +msgid "root mean squared error (RMSE)" +msgstr "" + +msgid "1 - area under curve (AUC)" +msgstr "" + +msgid "cross entropy" +msgstr "" + +msgid "Mean dropout loss (defined as %1$s) is based on %2$s permutations." +msgstr "" + +msgid "The target variable should have at least 2 classes." +msgstr "" + +msgid "Linear Discriminant Coefficients" +msgstr "" + +msgid "(Constant)" +msgstr "" + +msgid "Prior and Posterior Class Probabilities" +msgstr "" + +msgid "Prior" +msgstr "" + +msgid "Posterior" +msgstr "" + +msgid "Class Means in Training Data" +msgstr "" + +msgid "Linear Discriminant Matrix" +msgstr "" + +msgid "Tests of Equality of Class Means" +msgstr "" + +msgid "The null hypothesis specifies equal class means." +msgstr "" + +msgid "Tests of Equality of Covariance Matrices" +msgstr "" + +msgid "df" +msgstr "" + +msgid "p" +msgstr "" + +msgid "The null hypothesis specifies equal covariance matrices." +msgstr "" + +msgid "There are one or more levels in the target variable with less than two observations." +msgstr "" + +msgid "Box's M" +msgstr "" + +msgid "Pooled Within-Class Matrices Correlations" +msgstr "" + +msgid "Tests for Multivariate Normality" +msgstr "" + +msgid "Statistic" +msgstr "" + +msgid "Skewness" +msgstr "" + +msgid "Kurtosis" +msgstr "" + +msgid "Both p-values of the skewness and kurtosis statistics should be > 0.05 to conclude multivariate normality." +msgstr "" + +msgid "An error occurred when creating this table: %s" +msgstr "" + +msgid "Regression Coefficients" +msgstr "" + +msgid "Coefficient (%s)" +msgstr "" + +msgid "Standard Error" +msgstr "" + +msgid "z" +msgstr "" + +msgid "%1$s%% Confidence interval" +msgstr "" + +msgid "Lower" +msgstr "" + +msgid "Upper" +msgstr "" + +msgid "The regression coefficients for numeric features are standardized." +msgstr "" + +msgid "The regression coefficients are unstandardized." +msgstr "" + +msgid "Regression equation:\n%1$s" +msgstr "" + +msgid "Posterior Statistics" +msgstr "" + +msgid "Feature: %1$s" +msgstr "" + +msgid "Mean" +msgstr "" + +msgid "Std. deviation" +msgstr "" + +msgid "The table displays the mean and standard deviation of the feature given the target class." +msgstr "" + +msgid "The table displays the conditional probabilities given the target class." +msgstr "" + +msgid "Analysis not possible: The algorithm did not converge within the maximum number of training repetitions (%1$s)." +msgstr "" + +msgid "Optimizing network topology" +msgstr "" + +msgid "K-Distance Plot" +msgstr "" + +msgid "Points Sorted by Distance" +msgstr "" + +msgid "%s-Nearest Neighbors \nDistance" +msgstr "" + +msgid "Maximum curvature = %s" +msgstr "" + +msgid "End of recursion reached without converging" +msgstr "" + +msgid "x and y must be numeric and finite. Missing values not allowed." +msgstr "" + +msgid "x and y must be of equal length." +msgstr "" + +msgid "Need more points to find cutoff." +msgstr "" + +msgid "Need to specify fraction of maximum slope." +msgstr "" + +msgid "Fraction of maximum slope must be positive and be less than or equal to 1." +msgstr "" + +msgid "Method must be either 'first' or 'curvature'." +msgstr "" + +msgid "Cutoff point is beyond range. Returning NA." +msgstr "" + +msgid "Dendrogram" +msgstr "" + +msgid "The %1$s-component %2$s model could not be fitted, try a different model or a different number of clusters." +msgstr "" + +msgid "Estimated Model Parameters" +msgstr "" + +msgid "Mixing Probabilities" +msgstr "" + +msgid "Mixing probability" +msgstr "" + +msgid "Component %1$s" +msgstr "" + +msgid "Means" +msgstr "" + +msgid "Covariance Matrix for Component %1$s" +msgstr "" + +msgid "Scale of the Covariance" +msgstr "" + +msgid "Scale" +msgstr "" + +msgid "Shape of the Covariance Matrix" +msgstr "" + +msgid "Eigenvalues of the Covariance Matrix for Component %1$s" +msgstr "" + +msgid "Feature Importance" +msgstr "" + +msgid "Mean decrease in Gini Index" +msgstr "" + +msgid "K-nearest neighbors" +msgstr "" + +msgid "Linear discriminant" +msgstr "" + +msgid "Linear" +msgstr "" + +msgid "Boosting" +msgstr "" + +msgid "Random forest" +msgstr "" + +msgid "Regularized linear regression" +msgstr "" + +msgid "Neural network" +msgstr "" + +msgid "Decision tree" +msgstr "" + +msgid "Support vector machine" +msgstr "" + +msgid "Naive Bayes" +msgstr "" + +msgid "Logistic regression" +msgstr "" + +msgid "Multinomial regression" +msgstr "" + +msgid "Error: The trained model is not created in JASP." +msgstr "" + +msgid "The trained model (type: %1$s) is currently not supported in JASP." +msgstr "" + +msgid "Error: The trained model is created using a different version of JASP." +msgstr "" + +msgid "Loaded Model" +msgstr "" + +msgid "Classification" +msgstr "" + +msgid "Regression" +msgstr "" + +msgid "Loaded Model: %1$s" +msgstr "" + +msgid "The features in the new data are unscaled, consistent with the training set." +msgstr "" + +msgid "The features in the new data are scaled the same as those in the training set." +msgstr "" + +msgid "The trained model is not applied because the the following features are missing: %1$s." +msgstr "" + +msgid "The following features are unused because they are not a feature variable in the trained model: %1$s." +msgstr "" + +msgid "Nearest Neighbors" +msgstr "" + +msgid "n(New)" +msgstr "" + +msgid "Binomial" +msgstr "" + +msgid "Multinomial" +msgstr "" + +msgid "Logit" +msgstr "" + +msgid "Predictions for New Data" +msgstr "" + +msgid "Relative Influence" +msgstr "" + +msgid "Warning." +msgstr "" + +msgid "An error occurred when computing the mean dropout loss: %1$s" +msgstr "" + +msgid "Out-of-bag Improvement Plot" +msgstr "" + +msgid "Training set" +msgstr "" + +msgid "OOB Change in \n Multinomial Deviance" +msgstr "" + +msgid "OOB Change in \n Binomial Deviance" +msgstr "" + +msgid "OOB Change in \n%s Deviance" +msgstr "" + +msgid "Plotting not possible: The model is based on only a single tree." +msgstr "" + +msgid "Number of Trees" +msgstr "" + +msgid "Deviance Plot" +msgstr "" + +msgid "Multinomial Deviance" +msgstr "" + +msgid "Binomial Deviance" +msgstr "" + +msgid "%s Deviance" +msgstr "" + +msgid "Relative Influence Plot" +msgstr "" + +msgid "The minimum number of observations per node is too large. Ensure that `2 * Min. observations in node (%1$i) + 1` < `Training data used per tree (%2$s) * available training data (%3$i)` (in this case the minimum can be %4$i at most)." +msgstr "" + +msgid "Relative Importance" +msgstr "" + +msgid "No splits were made in the tree." +msgstr "" + +msgid "Splits in Tree" +msgstr "" + +msgid "Obs. in Split" +msgstr "" + +msgid "Split Point" +msgstr "" + +msgid "Improvement" +msgstr "" + +msgid "For each level of the tree, only the split with the highest improvement in deviance is shown." +msgstr "" + +msgid "Decision Tree Plot" +msgstr "" + +msgid "Plotting not possible: No splits were made in the tree." +msgstr "" + +msgid "Plotting not possible: An error occurred while creating this plot: %s" +msgstr "" + +msgid "Classification Accuracy Plot" +msgstr "" + +msgid "Mean Squared Error Plot" +msgstr "" + +msgid "Classification Accuracy" +msgstr "" + +msgid "Mean Squared Error" +msgstr "" + +msgid "Validation set" +msgstr "" + +msgid "Complexity Penalty" +msgstr "" + +msgid "Number of Nearest Neighbors" +msgstr "" + +msgid "Training and validation set" +msgstr "" + +msgid "Rectangular" +msgstr "" + +msgid "Triangular" +msgstr "" + +msgid "Epanechnikov" +msgstr "" + +msgid "Biweight" +msgstr "" + +msgid "Triweight" +msgstr "" + +msgid "Cosine" +msgstr "" + +msgid "Inverse" +msgstr "" + +msgid "Rank" +msgstr "" + +msgid "Optimal" +msgstr "" + +msgid "%1$s Weight Function" +msgstr "" + +msgid "Plotting not possible: The selected weighting scheme cannot be visualized separately from the data." +msgstr "" + +msgid "Proportion of Max. Distance" +msgstr "" + +msgid "Relative Weight" +msgstr "" + +msgid "Network Weights" +msgstr "" + +msgid "Node" +msgstr "" + +msgid "Layer" +msgstr "" + +msgid "Weight" +msgstr "" + +msgid "linear" +msgstr "" + +msgid "binary step" +msgstr "" + +msgid "logistic sigmoid" +msgstr "" + +msgid "sine" +msgstr "" + +msgid "cosine" +msgstr "" + +msgid "inverse tangent" +msgstr "" + +msgid "hyperbolic tangent" +msgstr "" + +msgid "rectified linear unit (ReLU)" +msgstr "" + +msgid "softplus" +msgstr "" + +msgid "softsign" +msgstr "" + +msgid "exponential linear unit (ELU)" +msgstr "" + +msgid "leaky rectified linear unit (Leaky ReLU)" +msgstr "" + +msgid "sigmoid linear unit (SiLU)" +msgstr "" + +msgid "mish" +msgstr "" + +msgid "gaussian" +msgstr "" + +msgid "gaussian error linear unit (GeLU)" +msgstr "" + +msgid "The weights are input for the %1$s activation function." +msgstr "" + +msgid "Network Structure Plot" +msgstr "" + +msgid "Intercept" +msgstr "" + +msgid "Input layer" +msgstr "" + +msgid "Output layer" +msgstr "" + +msgid "Hidden layer %1$s" +msgstr "" + +msgid "Binary" +msgstr "" + +msgid "Logistic Sigmoid" +msgstr "" + +msgid "Sine" +msgstr "" + +msgid "Inverse Tangent" +msgstr "" + +msgid "Hyperbolic Tangent" +msgstr "" + +msgid "ReLU" +msgstr "" + +msgid "Softplus" +msgstr "" + +msgid "Softsign" +msgstr "" + +msgid "ELU" +msgstr "" + +msgid "Leaky ReLU" +msgstr "" + +msgid "SiLU" +msgstr "" + +msgid "Mish" +msgstr "" + +msgid "GeLU" +msgstr "" + +msgid "%1$s Activation Function" +msgstr "" + +msgid "Input" +msgstr "" + +msgid "Output" +msgstr "" + +msgid "Generation" +msgstr "" + +msgid "Mean decrease in accuracy" +msgstr "" + +msgid "Total increase in node purity" +msgstr "" + +msgid "Out-of-bag Classification Accuracy Plot" +msgstr "" + +msgid "Out-of-bag Mean Squared Error Plot" +msgstr "" + +msgid "Out-of-bag %sClassification Accuracy" +msgstr "" + +msgid "Out-of-bag %sMean Squared Error" +msgstr "" + +msgid "Mean Decrease in Accuracy" +msgstr "" + +msgid "Total Increase in Node Purity" +msgstr "" + +msgid "L2 (Ridge)" +msgstr "" + +msgid "L1 (Lasso)" +msgstr "" + +msgid "Elastic Net" +msgstr "" + +msgid "Variable Trace Plot" +msgstr "" + +msgid "Coefficients" +msgstr "" + +msgid "Lambda Evaluation Plot" +msgstr "" + +msgid "Cross-Validated %sMean Squared Error" +msgstr "" + +msgid "Min. CV MSE" +msgstr "" + +msgid "%s 1 SE" +msgstr "" + +msgid "Row" +msgstr "" + +msgid "Cost of Constraints Violation" +msgstr "" From 464cfbcdd4d31625ef80633c9d5d6bd33412d8e3 Mon Sep 17 00:00:00 2001 From: ecadrian Date: Fri, 3 Oct 2025 16:45:45 +0200 Subject: [PATCH 2/2] Translated using Weblate (Galician) Currently translated at 100.0% (424 of 424 strings) Translation: JASP/jaspMachineLearning-R Translate-URL: https://hosted.weblate.org/projects/jasp/jaspmachinelearning-r/gl/ --- po/R-gl.po | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/po/R-gl.po b/po/R-gl.po index b462c6aa..45b8f9a1 100644 --- a/po/R-gl.po +++ b/po/R-gl.po @@ -7,7 +7,7 @@ msgid "" msgstr "" "Project-Id-Version: \n" "POT-Creation-Date: 2025-06-28 03:36\n" -"PO-Revision-Date: 2025-07-26 07:50+0000\n" +"PO-Revision-Date: 2025-10-03 17:32+0000\n" "Last-Translator: ecadrian \n" "Language-Team: Galician \n" @@ -16,7 +16,7 @@ msgstr "" "Content-Type: text/plain; charset=UTF-8\n" "Content-Transfer-Encoding: 8bit\n" "Plural-Forms: nplurals=2; plural=n != 1;\n" -"X-Generator: Weblate 5.13-dev\n" +"X-Generator: Weblate 5.14-dev\n" "X-Virgin-Header: remove this line if you change anything in the header.\n" "X-Language: gl_ES\n" "X-Source-Language: C\n" @@ -771,14 +771,14 @@ msgid "" "Displayed values represent feature contributions to the predicted value " "without features (column 'Base') for the test set." msgstr "" -"Os valores amosados representan as achegas de características ao valor " +"Os valores presentados representan as achegas de características ao valor " "predito sen particularidades (columna 'Base') para o conxunto de probas." msgid "" "Displayed values represent feature contributions to the predicted class " "probability without features (column 'Base') for the test set." msgstr "" -"Os valores amosados representan as achegas de características á " +"Os valores presentados representan as achegas de características á " "probabilidade predita de clase sen particularidades (columna 'Base') para o " "conxunto de probas."