diff --git a/po/QML-de.po b/po/QML-de.po index 4f10865d..61e0951d 100644 --- a/po/QML-de.po +++ b/po/QML-de.po @@ -1,9 +1,15 @@ msgid "" msgstr "" +"PO-Revision-Date: 2025-11-03 08:51+0000\n" +"Last-Translator: Johannes Keyser \n" +"Language-Team: German \n" +"Language: de\n" "MIME-Version: 1.0\n" "Content-Type: text/plain; charset=UTF-8\n" "Content-Transfer-Encoding: 8bit\n" -"Plural-Forms: nplurals=2; plural=(n != 1);\n" +"Plural-Forms: nplurals=2; plural=n != 1;\n" +"X-Generator: Weblate 5.14.1-dev\n" "X-Language: de\n" "X-Source-Language: American English\n" "X-Qt-Contexts: true\n" @@ -977,7 +983,6 @@ msgstr "" "gesendet wurden. Es zeigt auch die Verbesserung der Devianz, die die " "Aufteilungen ergeben." -#, fuzzy msgctxt "AttemptedSplits|" msgid "Only show splits in tree" msgstr "Nur Aufteilungen im Baum anzeigen" @@ -1025,7 +1030,6 @@ msgctxt "AlgorithmicSettings|" msgid "Cosine" msgstr "Kosinus" -#, fuzzy msgctxt "AlgorithmicSettings|" msgid "Inverse" msgstr "Invers" @@ -1445,12 +1449,10 @@ msgctxt "ModelOptimization|" msgid "Uniform" msgstr "Gleichverteilung" -#, fuzzy msgctxt "ModelOptimization|" msgid "One-point" msgstr "Ein-Punkt" -#, fuzzy msgctxt "ModelOptimization|" msgid "Multi-point" msgstr "Multi-Punkt" @@ -2016,7 +2018,6 @@ msgid "Adds a row with the silhouette score of each cluster to the table." msgstr "" "Fügt eine Zeile mit dem Silhouette-Score jedes Clusters zur Tabelle hinzu." -#, fuzzy msgctxt "ClusterInfo|" msgid "Centers" msgstr "Zentren" diff --git a/po/QML-zh_Hant.po b/po/QML-zh_Hant.po index 5b54e1bb..b397513d 100644 --- a/po/QML-zh_Hant.po +++ b/po/QML-zh_Hant.po @@ -1,9 +1,15 @@ msgid "" msgstr "" +"PO-Revision-Date: 2025-11-03 08:51+0000\n" +"Last-Translator: 陳寬裕 \n" +"Language-Team: Chinese (Traditional Han script) \n" +"Language: zh_Hant\n" "MIME-Version: 1.0\n" "Content-Type: text/plain; charset=UTF-8\n" "Content-Transfer-Encoding: 8bit\n" "Plural-Forms: nplurals=1; plural=0;\n" +"X-Generator: Weblate 5.14.1-dev\n" "X-Language: zh_Hant\n" "X-Qt-Contexts: true\n" @@ -331,7 +337,7 @@ msgstr "圖" msgctxt "mlClusteringHierarchical|" msgid "Dendrogram" -msgstr "" +msgstr "樹狀圖" msgctxt "mlClusteringHierarchical|" msgid "Training Parameters" @@ -348,19 +354,19 @@ msgstr "歐幾里得" msgctxt "mlClusteringHierarchical|" msgid "Average" -msgstr "平均" +msgstr "平均距離法" msgctxt "mlClusteringHierarchical|" msgid "Single" -msgstr "" +msgstr "最短距離法" msgctxt "mlClusteringHierarchical|" msgid "Complete" -msgstr "" +msgstr "最長距離法" msgctxt "mlClusteringHierarchical|" msgid "Centroid" -msgstr "" +msgstr "群中心距離法" msgctxt "mlClusteringHierarchical|" msgid "Median" @@ -368,15 +374,15 @@ msgstr "中位數" msgctxt "mlClusteringHierarchical|" msgid "Ward.D" -msgstr "" +msgstr "華德法" msgctxt "mlClusteringHierarchical|" msgid "Ward.D2" -msgstr "" +msgstr "第二代華德法" msgctxt "mlClusteringHierarchical|" msgid "McQuitty" -msgstr "" +msgstr "McQuitty 法" #, fuzzy msgctxt "mlClusteringKMeans|" @@ -653,7 +659,7 @@ msgstr "皮爾森" msgctxt "mlClusteringHierarchical|" msgid "Linkage" -msgstr "" +msgstr "集群方法" msgctxt "mlClusteringKMeans|" msgid "Max. iterations" @@ -1812,7 +1818,7 @@ msgstr "" msgctxt "DecisionBoundary|" msgid "Add data points" -msgstr "" +msgstr "新增資料點" msgctxt "DecisionBoundary|" msgid "Show the observations in the data set as points in the plot." @@ -1829,6 +1835,9 @@ msgid "" "optimal number of clusters. The plot shows three curves using AIC, BIC, and " "'elbow method' optimization." msgstr "" +"生成一個圖表，圖的 Y 軸為群內平方和總和（total within sum of squares），X 軸" +"為群數（number of clusters）。這個圖可用來判斷最佳群數。圖中會顯示三條曲線，" +"分別依據 AIC、BIC 以及手肘部法（elbow method）進行最佳化。" msgctxt "PredictivePerformance|" msgid "Predictive performance" @@ -1864,6 +1873,11 @@ msgid "" "across several clustering analyses you can set their seed to the same value, " "as the t-SNE algorithm uses random starting values." msgstr "" +"生成集群結果的 t-SNE 圖。t-SNE 圖可用於將高維資料投影到二維空間，以視覺化資料" +"點之間的相對距離。由於 t-SNE 的二維空間坐標沒有明確的數值意義，因此軸本身不可" +"解釋。t-SNE 圖的目的是呈現觀測值與群之間的相對距離印象。若想在多次集群分析中" +"生成相同的 t-SNE 圖，可以將隨機起點(或稱種子，seed）設為相同，因為 t-SNE 演算" +"法會使用隨機的起始值。" #, fuzzy msgctxt "Tsne|" @@ -1876,13 +1890,13 @@ msgstr "" msgctxt "Tsne|" msgid "Add data labels" -msgstr "" +msgstr "新增資料標籤" msgctxt "Tsne|" msgid "" "Add the row numbers of the observations in the data set as labels to the " "plot." -msgstr "" +msgstr "將資料集中各觀測值的列號（row numbers）作為標籤，加入到圖中。" #, fuzzy msgctxt "ClassProportions|" @@ -1919,7 +1933,7 @@ msgstr "" msgctxt "ClusterInfo|" msgid "Silhouette score" -msgstr "輪廓係數" +msgstr "輪廓係數(Silhouette)" msgctxt "ClusterInfo|" msgid "Adds a row with the silhouette score of each cluster to the table." @@ -2016,7 +2030,7 @@ msgstr "集群決策" msgctxt "ClusterDetermination|" msgid "Choose how to determine the number of clusters in the model." -msgstr "" +msgstr "選擇用何種方式來決定模型中的集群數量。" #, fuzzy msgctxt "ClusterDetermination|" @@ -2027,7 +2041,8 @@ msgctxt "ClusterDetermination|" msgid "" "Enables you to generate a fixed amount of clusters. This allows you to " "generate your own specified number of clusters, and thus, optimize manually." -msgstr "" +msgstr "可讓你生成固定數量的集群。這表示你可以自行指定要分成的集群，並以此手動進行最" +"佳化。" msgctxt "ClusterDetermination|" msgid "Clusters" @@ -2035,7 +2050,7 @@ msgstr "集群數" msgctxt "ClusterDetermination|" msgid "The number of clusters to be fitted." -msgstr "" +msgstr "要擬合(或設定)的集群數量。" msgctxt "ClusterDetermination|" msgid "Optimized according to" @@ -2045,7 +2060,7 @@ msgctxt "ClusterDetermination|" msgid "" "Enables you to choose an optimization method. BIC optimization is set as " "default." -msgstr "" +msgstr "允許你選擇一種最佳化方法。系統預設使用 BIC 最佳化。" msgctxt "ClusterDetermination|" msgid "" @@ -2058,6 +2073,11 @@ msgid "" "uses the similarity of observations within a cluster and their dissimilarity " "to other clusters for optimizing the clustering output." msgstr "" +"最佳化方法的選項包括 AIC、BIC 和 Silhouette(輪廓係數)。AIC 是根據群內平方和(" +"群內變異量)、生成的群數，以及資料的維度數來最佳化群集結果。BIC 則是根據群內平" +"方和(群內變異量)、生成的群數、維度數，以及樣本大小來最佳化群集結果。" +"Silhouette(輪廓係數)則透過比較同一群內觀測值之間的相似程度，以及它們與其他群" +"之間的不相似程度，來評估並最佳化群集結果。" msgctxt "ClusterDetermination|" msgid "Max. clusters" @@ -2144,7 +2164,7 @@ msgstr "" msgctxt "ScaleVariables|" msgid "Scale features" -msgstr "特徵縮放" +msgstr "特徵標準化" msgctxt "ScaleVariables|" msgid "" @@ -2154,11 +2174,14 @@ msgid "" "the Z-score standardization of a mean of 0 and a standard deviation of 1. " "This option is selected by default." msgstr "" +"將資料集中的連續變數進行標準化。標準化的目的，是讓原本量尺不同的變數，其數值" +"能被轉換到相似的尺度範圍中。如此一來，可以提升數值運算的穩定性。JASP 採用 Z " +"分數標準化方式，將各變數轉換為平均數為 0、標準差為 1 的常態分配。此選項為預設" +"啟用。" -#, fuzzy msgctxt "SetSeed|" msgid "Set seed" -msgstr "設定種子值" +msgstr "設定隨機起點" msgctxt "SetSeed|" msgid "" @@ -2166,6 +2189,9 @@ msgid "" "exclude random processes influencing an analysis. For example, setting a " "seed makes it possible to re-run analyses with the same data splits." msgstr "" +"此選項可讓你為分析設定一個隨機起點(或稱種子，seed)。設定隨機起點後，可以排除" +"隨機過程對分析結果的影響。例如，設定隨機起點可讓你在重新執行分析時，使用相同" +"的資料分割方式，確保結果一致。" msgctxt "SetSeed|" msgid "The value of the seed."