underfitting risk
欠擬合風險
avoiding underfitting
避免欠擬合
susceptible to underfitting
易於欠擬合
underfitting problem
欠擬合問題
detecting underfitting
檢測欠擬合
model underfitting
模型欠擬合
underfitting data
欠擬合數據
prevent underfitting
預防欠擬合
checking for underfitting
檢查欠擬合
severe underfitting
嚴重的欠擬合
the model suffered from severe underfitting and failed to capture the underlying patterns.
模型存在嚴重的欠擬合現象，未能捕捉到潛在模式。
we noticed significant underfitting when evaluating the model on the test set.
在評估模型時，我們注意到明顯的欠擬合現象。
underfitting often results from using a model that is too simple for the data.
欠擬合通常是由於使用過於簡單的模型來處理數據所致。
to avoid underfitting, we increased the model complexity and added more features.
爲了避免欠擬合，我們增加了模型的複雜性並添加了更多特徵。
the linear regression model exhibited underfitting compared to the neural network.
與神經網絡相比，線性迴歸模型表現出欠擬合的現象。
underfitting leads to poor performance on both training and test data.
欠擬合會導致訓練數據和測試數據上的表現不佳。
we checked for underfitting by plotting the training and validation loss curves.
我們通過繪製訓練和驗證損失曲線來檢查是否存在欠擬合。
regularization can sometimes exacerbate underfitting if applied too aggressively.
如果過度應用，正則化有時會加劇欠擬合的現象。
the goal is to find a balance and avoid both underfitting and overfitting.
目標是找到平衡點，避免欠擬合和過擬合。
underfitting can be a consequence of insufficient training data or a poor feature set.
欠擬合可能是由於訓練數據不足或特徵集不佳造成的。
we used cross-validation to diagnose the extent of underfitting in the model.
我們使用交叉驗證來診斷模型中欠擬合的程度。
underfitting risk
欠擬合風險
avoiding underfitting
避免欠擬合
susceptible to underfitting
易於欠擬合
underfitting problem
欠擬合問題
detecting underfitting
檢測欠擬合
model underfitting
模型欠擬合
underfitting data
欠擬合數據
prevent underfitting
預防欠擬合
checking for underfitting
檢查欠擬合
severe underfitting
嚴重的欠擬合
the model suffered from severe underfitting and failed to capture the underlying patterns.
模型存在嚴重的欠擬合現象，未能捕捉到潛在模式。
we noticed significant underfitting when evaluating the model on the test set.
在評估模型時，我們注意到明顯的欠擬合現象。
underfitting often results from using a model that is too simple for the data.
欠擬合通常是由於使用過於簡單的模型來處理數據所致。
to avoid underfitting, we increased the model complexity and added more features.
爲了避免欠擬合，我們增加了模型的複雜性並添加了更多特徵。
the linear regression model exhibited underfitting compared to the neural network.
與神經網絡相比，線性迴歸模型表現出欠擬合的現象。
underfitting leads to poor performance on both training and test data.
欠擬合會導致訓練數據和測試數據上的表現不佳。
we checked for underfitting by plotting the training and validation loss curves.
我們通過繪製訓練和驗證損失曲線來檢查是否存在欠擬合。
regularization can sometimes exacerbate underfitting if applied too aggressively.
如果過度應用，正則化有時會加劇欠擬合的現象。
the goal is to find a balance and avoid both underfitting and overfitting.
目標是找到平衡點，避免欠擬合和過擬合。
underfitting can be a consequence of insufficient training data or a poor feature set.
欠擬合可能是由於訓練數據不足或特徵集不佳造成的。
we used cross-validation to diagnose the extent of underfitting in the model.
我們使用交叉驗證來診斷模型中欠擬合的程度。
探索常見搜尋詞彙