average error

简明释义

平均误差

英英释义

例句

1.The average error 平均误差 in our sales predictions was lower than last year's figures.

我们销售预测中的平均误差 average error 低于去年的数据。

2.The model's performance improved significantly after we reduced the average error 平均误差 to below 5%.

在我们将平均误差 average error 降低到5%以下后，模型的性能显著提高。

3.In our study, we calculated the average error 平均误差 for each algorithm to evaluate their accuracy.

在我们的研究中，我们计算了每个算法的平均误差 average error 以评估它们的准确性。

4.To improve the system, we need to analyze the sources of average error 平均误差 in our measurements.

为了改善系统，我们需要分析我们测量中的平均误差 average error 的来源。

5.The average error 平均误差 of the GPS readings was within acceptable limits.

GPS读数的平均误差 average error 在可接受范围内。

作文

In the world of data analysis and statistics, understanding various metrics is crucial for accurate interpretation. One such important metric is the average error, which serves as a measure of how far predicted values deviate from actual values. The average error can provide insight into the reliability of a model or method used in forecasting or predictions. It is calculated by taking the sum of the absolute differences between the predicted values and the actual values, and then dividing that sum by the number of observations. This gives us a clear picture of the average deviation, or error, across all data points.For instance, in a business context, a company may use a predictive model to forecast sales for the upcoming quarter. If the average error of the forecasts is low, it indicates that the model is performing well and the predictions are close to the actual sales figures. Conversely, a high average error suggests that the model may need adjustments or that external factors are influencing the outcomes in ways that were not accounted for.Moreover, the average error is particularly useful when comparing different models or approaches. By calculating the average error for each model, analysts can determine which one provides the most accurate predictions. This comparative analysis can be vital for businesses that rely on precise forecasting to make strategic decisions.It is also important to note that while the average error is a valuable metric, it does have its limitations. For example, it treats all errors equally without considering their direction. This means that positive and negative errors cancel each other out, potentially leading to a misleading impression of accuracy. Therefore, it is often beneficial to complement the average error with other metrics such as the mean squared error (MSE) or root mean squared error (RMSE) for a more comprehensive evaluation of model performance.In conclusion, the average error is a fundamental concept in data analysis that helps quantify the accuracy of predictions. By understanding and utilizing this metric, individuals and organizations can improve their forecasting methods and make more informed decisions based on reliable data. As we continue to navigate an increasingly data-driven world, mastering concepts like the average error will be essential for success in various fields, from business to science and beyond.

在数据分析和统计的世界中，理解各种指标对于准确解读至关重要。其中一个重要的指标是平均误差，它作为预测值与实际值偏差的度量。平均误差可以提供对所使用的模型或方法在预测或预报中的可靠性的洞察。它的计算方法是将预测值与实际值之间的绝对差的总和，然后将该总和除以观察数量。这为我们提供了所有数据点的平均偏差或误差的清晰图像。例如，在商业环境中，公司可能会使用预测模型来预测即将到来的季度销售。如果预测的平均误差较低，则表明该模型表现良好，预测值接近实际销售数字。相反，高平均误差则表明该模型可能需要调整，或者外部因素以未考虑的方式影响结果。此外，平均误差在比较不同模型或方法时特别有用。通过计算每个模型的平均误差，分析师可以确定哪个模型提供了最准确的预测。这种比较分析对于依赖精确预测来做出战略决策的企业来说至关重要。同样重要的是要注意，虽然平均误差是一个有价值的指标，但它也有其局限性。例如，它平等对待所有误差，而不考虑其方向。这意味着正误差和负误差相互抵消，可能导致对准确性的误导性印象。因此，通常有必要用其他指标（如均方误差（MSE）或均方根误差（RMSE））来补充平均误差，以更全面地评估模型性能。总之，平均误差是数据分析中的一个基本概念，有助于量化预测的准确性。通过理解和利用这一指标，个人和组织可以改善其预测方法，并根据可靠数据做出更明智的决策。随着我们继续在一个日益数据驱动的世界中航行，掌握像平均误差这样的概念将对各个领域的成功至关重要，从商业到科学及其他领域。