To avoid bias in the data and improve the model's generalization performance, it is necessary to carefully mix samples from different sources.
为了避免数据偏差并提高模型的泛化性能，需要谨慎地混合来自不同来源的样本。
為了避免資料偏頗並提升模型的泛化能力，需要謹慎地混合來自不同來源的樣本。
データの偏りを避け、、モデルの汎化性能を高めるためにに、、異なる出典からのサンプルを慎重にに交ぜることがが求められるられる。。
Để tránh sự thiên lệch dữ liệu và nâng cao khả năng khái quát hóa của mô hình, cần phải cẩn trọng khi pha trộn các mẫu từ các nguồn khác nhau.
Upang maiwasan ang pagkiling ng datos at mapabuti ang kakayahan ng modelo na mag-generalize, kinakailangang maingat na paghaluin ang mga halimbawa mula sa iba't ibang pinagmulan.
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To avoid bias in the data and improve the model's generalization performance, it is necessary to carefully mix samples from different sources.
To avoid bias in the data and improve the model's generalization performance, it is necessary to carefully mix samples from different sources.
データの偏りを避け、モデルの汎化性能を高めるために、異なる出典からのサンプルを慎重に交ぜることが求められる。
Related words
交ぜる
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