MSE的意思、翻譯和例句

是什麼意思

「MSE」通常是指「均方誤差」（Mean Squared Error），這是一種用於評估預測模型準確性的重要指標。它計算預測值與實際值之間的差異的平方的平均值。MSE越小，表示模型的預測能力越好。

依照不同程度的英文解釋

  1. A way to see how good a prediction is.
  2. A number that shows how far off predictions are.
  3. A measure of how wrong a prediction was.
  4. A calculation that helps to understand prediction errors.
  5. A statistic that indicates the average squared difference between predicted and actual values.
  6. A metric used to quantify the accuracy of a predictive model.
  7. A mathematical calculation that assesses the performance of a model by measuring its prediction errors.
  8. An evaluation tool that quantifies the average of the squares of errors between predicted values and actual values.
  9. A fundamental statistical measure that reflects the average squared deviations of predicted values from actual outcomes.
  10. A widely used metric in statistics and machine learning for assessing prediction accuracy.

相關英文單字或片語的差別與用法

1：Mean Squared Error

用法：

在統計學和機器學習中，均方誤差是一種常用的損失函數，用於評估模型的預測準確性。它通過計算預測值與實際值之間的差的平方的平均值來量化誤差。這個指標在回歸分析中尤其重要，因為它能夠反映出模型在預測上的表現。

例句及翻譯：

例句 1：

我們使用均方誤差來評估模型的預測準確性。

We use mean squared error to evaluate the accuracy of the model's predictions.

例句 2：

較低的均方誤差表示模型的預測效果更好。

A lower mean squared error indicates better predictive performance of the model.

例句 3：

在訓練過程中，我們持續監控均方誤差的變化。

During the training process, we continuously monitor the changes in mean squared error.

輸入或選擇一個中文或英文單字或片語：