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13 changes: 7 additions & 6 deletions po/QML-de.po
Original file line number Diff line number Diff line change
@@ -1,9 +1,15 @@
msgid ""
msgstr ""
"PO-Revision-Date: 2025-11-03 08:51+0000\n"
"Last-Translator: Johannes Keyser <[email protected]>\n"
"Language-Team: German <https://hosted.weblate.org/projects/jasp/"
"jaspmachinelearning-qml/de/>\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"
Expand Down Expand Up @@ -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"
Expand Down Expand Up @@ -1025,7 +1030,6 @@ msgctxt "AlgorithmicSettings|"
msgid "Cosine"
msgstr "Kosinus"

#, fuzzy
msgctxt "AlgorithmicSettings|"
msgid "Inverse"
msgstr "Invers"
Expand Down Expand Up @@ -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"
Expand Down Expand Up @@ -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"
Expand Down
66 changes: 46 additions & 20 deletions po/QML-zh_Hant.po
Original file line number Diff line number Diff line change
@@ -1,9 +1,15 @@
msgid ""
msgstr ""
"PO-Revision-Date: 2025-11-03 08:51+0000\n"
"Last-Translator: 陳寬裕 <[email protected]>\n"
"Language-Team: Chinese (Traditional Han script) <https://hosted.weblate.org/"
"projects/jasp/jaspmachinelearning-qml/zh_Hant/>\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"

Expand Down Expand Up @@ -331,7 +337,7 @@ msgstr "圖"

msgctxt "mlClusteringHierarchical|"
msgid "Dendrogram"
msgstr ""
msgstr "樹狀圖"

msgctxt "mlClusteringHierarchical|"
msgid "Training Parameters"
Expand All @@ -348,35 +354,35 @@ 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"
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|"
Expand Down Expand Up @@ -653,7 +659,7 @@ msgstr "皮爾森"

msgctxt "mlClusteringHierarchical|"
msgid "Linkage"
msgstr ""
msgstr "集群方法"

msgctxt "mlClusteringKMeans|"
msgid "Max. iterations"
Expand Down Expand Up @@ -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."
Expand All @@ -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"
Expand Down Expand Up @@ -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|"
Expand All @@ -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|"
Expand Down Expand Up @@ -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."
Expand Down Expand Up @@ -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|"
Expand All @@ -2027,15 +2041,16 @@ 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"
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"
Expand All @@ -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 ""
Expand All @@ -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"
Expand Down Expand Up @@ -2144,7 +2164,7 @@ msgstr ""

msgctxt "ScaleVariables|"
msgid "Scale features"
msgstr "特徵縮放"
msgstr "特徵標準化"

msgctxt "ScaleVariables|"
msgid ""
Expand All @@ -2154,18 +2174,24 @@ 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 ""
"Gives the option to set a seed for your analysis. Setting a seed will "
"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."
Expand Down