diff --git a/i18n/si/msgs.jaml b/i18n/si/msgs.jaml
index 620faf7820..7c059d4ed4 100644
--- a/i18n/si/msgs.jaml
+++ b/i18n/si/msgs.jaml
@@ -202,9 +202,9 @@ util.py:
def `funcv`:
unsafe: false
version.py:
- 3.37.0: false
- 3.37.0.dev0+f49e020: false
- f49e020957eaf15fea4bab426141dd2942f9deac: false
+ 3.38.0: false
+ 3.38.0.dev0+c767157: false
+ c7671579ac399d27a1b5fb21c31f870448db9ed8: false
.dev: false
canvas/__main__.py:
ORANGE_STATISTICS_API_URL: false
@@ -858,6 +858,7 @@ data/domain.py:
_variables: false
_indices: false
_hash: false
+ _eq_cache: false
def `from_numpy`:
def `get_name`:
{} {:0{}}: false
@@ -2192,6 +2193,8 @@ evaluation/testing.py:
test_data: false
def `fit`:
Validation.fit is deprecated; use the call operator: false
+ def `_collect_part_results`:
+ Multiple targets are not supported.: Večrazredni problemi niso podprti.
class `CrossValidation`:
def `get_indices`:
Using non-stratified sampling.: false
@@ -2352,11 +2355,6 @@ misc/lazy_module.py:
def `_do_import`:
Orange.: false
Orange: false
-misc/openpyxl_patch.py:
- def `read_worksheets`:
- "Cell '{0}':{1} is part of a merged range but has a comment which will ": false
- be removed because merged cells cannot contain any data.: false
- chartsheet: false
misc/server_embedder.py:
TaskItem: false
id: false
@@ -3004,41 +3002,15 @@ projection/pca.py:
SparsePCA: false
IncrementalPCA: false
TruncatedSVD: false
- def `randomized_pca`:
- auto: false
- f: false
- economic: false
- class `ImprovedPCA`:
- def `_fit`:
- csr: false
- csc: false
- arpack: false
- auto: false
- randomized: false
- mle: false
- full: false
- only the randomized solver supports sparse matrices: false
- Unrecognized svd_solver='{0}': false
- def `_fit_truncated`:
- n_components=%r cannot be a string with svd_solver='%s': false
- 'n_components=%r must be between 1 and min(n_samples, ': false
- n_features)=%r with svd_solver='%s': false
- 'n_components=%r must be of type int when greater than or ': false
- equal to 1, was of type=%r: false
- arpack: false
- 'n_components=%r must be strictly less than min(n_samples, ': false
- randomized: false
- def `transform`:
- mean_: false
- components_: false
- csr: false
- csc: false
class `PCA`:
PCA: false
def `__init__`:
auto: false
def `fit`:
n_components: false
+ svd_solver: false
+ auto: false
+ arpack: false
class `SparsePCA`:
Sparse PCA: false
def `__init__`:
@@ -3183,6 +3155,41 @@ regression/neural_network.py:
class `NNRegressionLearner`:
def `_initialize_wrapped`:
callback: false
+regression/pls.py:
+ PLSRegressionLearner: false
+ class `PLSModel`:
+ PLS T: false
+ PLS U: false
+ def `__str__`:
+ PLSModel {self.skl_model}: false
+ def `_get_var_names`:
+ {prefix}{postfix}: false
+ def `project`:
+ PLSModel can only project tables: false
+ def `components`:
+ components: false
+ Component {i + 1}: false
+ def `coefficients_table`:
+ coef {i}: false
+ name: false
+ coefficients: false
+ def `residuals_normal_probability`:
+ {name} ({var.name}): false
+ Sample Quantiles: Vzorčni kvantili:
+ Theoretical Quantiles: Teoretični kvantili:
+ residuals normal probability: verjetnosti residualov
+ def `dmodx`:
+ DModX: false
+ DMod: false
+ class `PLSRegressionLearner`:
+ def `fit`:
+ n_components: false
+ def `incompatibility_reason`:
+ Numeric targets expected.: false
+ Only numeric target variables expected.: false
+ __main__: false
+ housing: false
+ 'learner: {learner}\nRMSE: {ca}\n': true
regression/random_forest.py:
RandomForestRegressionLearner: false
class `RandomForestRegressor`:
@@ -5400,12 +5407,6 @@ widgets/data/owdiscretize.py:
widgets/data/oweditdomain.py:
V: false
H: false
- class `_DataType`:
- def `name_type`:
- Categorical: false
- Real: false
- Time: false
- String: false
class `Categorical`:
Categorical: false
name: false
@@ -5628,6 +5629,9 @@ widgets/data/oweditdomain.py:
Data: Podatki
class `Error`:
A variable name is duplicated.: Ime spremenljivke je podvojeno.
+ class `Warning`:
+ Failed to restore transform {} for column {}: Ne morem obnoviti transformacije {} za stolpec {}
+ Categories mapping for {} does not apply to current input: Preslikava kategorij za {} ne velja za trenutne podatke.
def `__init__`:
Variables: Spremenljivke
Edit: Uredi
@@ -5642,8 +5646,8 @@ widgets/data/oweditdomain.py:
Apply: Potrdi
button-apply: false
Apply changes and commit data on output.: Potrdi spremembe in pošlji podatke na izhod.
- def `_restore_transform`:
- 'Failed to restore transform: {t}, {err}': false
+ def `_restore`:
+ ', ': false
def `_set_modified`:
button-apply: false
def `send_report`:
@@ -5810,10 +5814,11 @@ Categorical features are passed as strings
class `FeatureItemDelegate`:
def `displayText`:
' := ': false
- class `FeatureConstructorHandler`:
- def `is_valid_item`:
- eval: false
- __GLOBALS: false
+ class `_FeatureConstructorHandler`:
+ def `initialize`:
+ descriptors: false
+ expressions_with_values: false
+ currentIndex: false
class `OWFeatureConstructor`:
Formula: true
'Construct new features (data columns) from a set of ': Sestavi nove značilke, izračunane
@@ -5829,9 +5834,9 @@ Categorical features are passed as strings
Categorical feature {} needs more values.: Kategorična spremenljivka {} potrebuje več vrednosti.
'Invalid expressions: {}.': Nepravilen izraz: {}
{}: false
- class `Warning`:
- 'Recently added variable has been renamed, ': 'Nove spremenljivke so preimenovane '
- to avoid duplicates.\n: zaradi ponovljenih imen.
+ class `Information`:
+ 'A new variable that is named the same as an existing one will ': 'Nova spremenljivka z enakim imenom kot obstoječa bo '
+ replace it on the output.: zamenjala obstoječo.
def `__init__`:
Variable Definitions: Definicije spremenljivk
New: Nova
@@ -8917,6 +8922,80 @@ widgets/evaluate/owliftcurve.py:
array dimensions don't match: false
mergesort: false
__main__: false
+widgets/evaluate/owpermutationplot.py:
+ def `permutation`:
+ Calculating...: Računam...
+ class `ParameterSetter`:
+ Gridlines: Mrežne črte
+ Show: Pokaži
+ def `axis_items`:
+ item: false
+ class `PermutationPlot`:
+ def `__init__`:
+ Correlation between original Y and permuted Y (%): Korelacija med izvirno Y in permutiranim Y (%)
+ bottom: false
+ def `set_data`:
+ left: false
+ AUC: true
+ '#000': false
+ '#333': false
+ pen: false
+ symbol: false
+ o: false
+ brush: false
+ '#6fa255': false
+ s: false
+ '#3a78b6': false
+ size: false
+ hoverable: false
+ tip: false
+ 'x: {x:.3g}\ny: {y:.3g}': false
+ Train: Testni
+ CV: Prečno preverjanje
+ class `OWPermutationPlot`:
+ Permutation Plot: Permutacijska krivulja
+ Permutation analysis plotting: Prikaz permutacijske analize
+ icons/PermutationPlot.svg: false
+ graph.plotItem: false
+ class `Inputs`:
+ Data: Podatki
+ Learner: Učni algoritem
+ class `Error`:
+ {}: false
+ At least {N_FOLD} instances are needed.: Potrebujemo vsaj {N_FOLD} primerov.
+ def `_add_controls`:
+ Settings: Nastavitve
+ n_permutations: false
+ Permutations:: Permutacije:
+ Info: Informacije
+ def `__set_info`:
+ No data available.: Ni podatkov.
+ '
+
+
+ |
+ Corr = 0 |
+ Corr = 100 |
+
+
+ | Train |
+ {intercept_tr:.4f} |
+ {y_tr:.4f} |
+
+
+ | CV |
+ {intercept_cv:.4f} |
+ {y_cv:.4f} |
+
+
+ ': false
+ def `send_report`:
+ Settings: Nastavitve
+ Permutations: Permutacije
+ Info: Informacije
+ Plot: Graf
+ __main__: false
+ iris: false
widgets/evaluate/owpredictions.py:
PredictorSlot: false
predictor: false
@@ -9449,7 +9528,7 @@ widgets/model/owadaboost.py:
iris: false
widgets/model/owcalibratedlearner.py:
class `OWCalibratedLearner`:
- Calibrated Learner: Kalibriran model
+ Calibrated Learner: Kalibriran učni algoritem
'Wraps another learner with probability calibration and ': 'Ovije drug učni algoritem z modelom za kalibracijo verjetnosti '
decision threshold optimization: in optimiranje klasifikacijskega praga.
icons/CalibratedLearner.svg: false
@@ -9933,6 +10012,43 @@ widgets/model/owneuralnetwork.py:
alpha_index: false
__main__: false
iris: false
+widgets/model/owpls.py:
+ class `OWPLS`:
+ PLS: true
+ Partial Least Squares Regression widget for multivariate data analysis: PLS regresija za multivariatno analizo podatkov
+ icons/PLS.svg: false
+ partial least squares: partial least squares, pls, regresija
+ class `Outputs`:
+ Coefficients and Loadings: Koeficienti in uteži
+ Data with Scores: Podatki z rezultati
+ Components: Komponente
+ class `Warning`:
+ 'Sparse input data: default preprocessing is to scale it.': 'Redki vhodni podatki: privzeta predobdelava je skaliranje.'
+ def `add_main_layout`:
+ Optimization Parameters: Optimizacijski parametri
+ n_components: false
+ 'Components: ': 'Komponente: '
+ max_iter: false
+ 'Iteration limit: ': 'Omejitev iteracij: '
+ scale: false
+ Scale features and target: Skaliraj spremenljivke in ciljno spremenljivko
+ def `_create_output_coeffs_loadings`:
+ coef ({v.name}): koef ({v.name})
+ coef/X_sd ({v.name}): koef/X_sd ({v.name})
+ w*c {i + 1}: true
+ Variable name: Ime spremenljivke
+ Variable role: Vloga spremenljivke
+ Feature: Značilka
+ Target: Cilj
+ intercept: odsek
+ Coefficients and Loadings: Koeficienti in uteži
+ def `set_data`:
+ Data has no target variable.\n: Podatki nimajo ciljne spremenljivke.\n
+ Select one with the Select Columns widget.: Izberite jo z gradnikom Izberi stolpce.
+ def `create_learner`:
+ preprocessors: false
+ __main__: false
+ housing: false
widgets/model/owrandomforest.py:
class `OWRandomForest`:
Random Forest: Naključni gozd
@@ -10303,6 +10419,8 @@ widgets/model/owsvm.py:
Polynomial, ({g:.4} x⋅y + {c:.4}){d}: Polinomsko, ({g:.4} x⋅y + {c:.4}){d}
RBF, exp(-{:.4}|x-y|²): true
Sigmoid, tanh({g:.4} x⋅y + {c:.4}): Sigmoidno, tanh({g:.4} x⋅y + {c:.4})
+ def `migrate_settings`:
+ degree: false
__main__: false
iris: false
widgets/model/owtree.py:
@@ -10830,6 +10948,7 @@ widgets/unsupervised/owdistances.py:
Pearson (absolute): Pearsonova (absolutna)
Absolute value of Pearson correlation; distance = 1 - |ρ|: Absolutna vrednost Pearsonove korelacije; razdalja = 1 - |ρ|
Spearman: Spearmanova
+ Spearman correlation; distance = 1 - ρ/2: Spearmanova korelacija; razdalja = 1 - ρ/2
Spearman (absolute): Spearmanova (absolutna)
Jaccard: Jaccardova
Jaccard distance: Jaccardova razdalja
@@ -10963,6 +11082,8 @@ widgets/unsupervised/owhierarchicalclustering.py:
Some data from the subset does not appear in distance matrix: Nekateri izmed primerov v vhodnih podatkih se ne pojavijo v matriki razdalj.
Subset data refers to a different table: Podmnožica podatkov pripada drugi tabeli podatkov.
Pruned cluster doesn't show colors and indicate subset: Porezano gručenje ne kaže barv in podmnožic.
+ 'Variables with too many values may ': 'Spremenljivke z veliko vrednostmi lahko '
+ degrade the performance of downstream widgets.: poslabšajo delovanje kasnejših gradnikov.
def `__init__`:
M: false
linkage: false
@@ -12379,6 +12500,11 @@ widgets/utils/messages.py:
MessageGroup: false
MessagesMixin: false
WidgetMessagesMixin: false
+widgets/utils/multi_target.py:
+ Multiple targets are not supported.: Večrazredni problemi niso podprti.
+ def `check_multiple_targets_input`:
+ def `new_f`:
+ multiple_targets_data: false
widgets/utils/overlay.py:
OverlayWidget: false
MessageWidget: false
@@ -14294,7 +14420,7 @@ widgets/visualize/owscatterplot.py:
label: false
def `update_reg_line_label_colors`:
label: false
- def `update_regression_line`:
+ def `_update_curve`:
'#505050': false
class `OWScatterPlot`:
Scatter Plot: Razsevni diagram
@@ -14317,6 +14443,9 @@ widgets/visualize/owscatterplot.py:
Treat variables as independent: Obravnavaj spremenljivki kot neodvisni
If checked, fit line to group (minimize distance from points);\n: Če je opcija izbrana, je črta postavljena čim bližje točkam;
otherwise fit y as a function of x (minimize vertical distances): sicer pa minimizira samo razdaljo v smeri y.
+ graph.show_ellipse: false
+ Show confidence ellipse: Prikaz elipse zaupanja
+ Hotelling's T² confidence ellipse (α=95%): Hotellingova elipsa zaupanja T² (α=95%)
def `_add_controls_axis`:
Axes: Osi
attr_x: false