aligned sample

简明释义

均衡采样;

英英释义

例句

1.To validate the findings, we utilized an aligned sample from multiple sources.

为了验证结果，我们使用了来自多个来源的对齐样本。

2.The aligned sample helped in minimizing bias during the analysis phase.

这个对齐样本在分析阶段帮助最小化了偏差。

3.The researchers collected an aligned sample to ensure the data was representative of the population.

研究人员收集了一个对齐样本以确保数据代表了总体。

4.The quality of the aligned sample directly impacted the reliability of the conclusions drawn.

这个对齐样本的质量直接影响了得出的结论的可靠性。

5.In the study, an aligned sample was used to compare the results across different demographics.

在这项研究中，使用了一个对齐样本来比较不同人口统计的结果。

作文

In the field of research and data analysis, the term aligned sample refers to a collection of data points that are organized in a manner that allows for effective comparison and analysis. This concept is particularly crucial in experiments where consistency and accuracy are paramount. An aligned sample ensures that all variables are controlled, allowing researchers to draw meaningful conclusions from their findings. For instance, in a clinical trial testing a new medication, an aligned sample might consist of participants who share similar characteristics such as age, gender, and health status. By aligning these samples, researchers can isolate the effects of the medication without interference from other factors.Furthermore, the importance of aligned samples extends beyond clinical research. In social sciences, for example, researchers often use aligned samples to study behaviors across different demographics. When analyzing survey results, having an aligned sample helps ensure that the data reflects the true opinions of a specific group rather than being skewed by outliers or irrelevant data points. This alignment is critical in drawing accurate conclusions and making informed decisions based on the data collected.Moreover, in the realm of machine learning, the concept of aligned samples plays a significant role in training algorithms. For a model to learn effectively, it needs to be trained on an aligned sample that accurately represents the problem space. If the training data is not aligned, the model may produce biased or inaccurate predictions, leading to poor performance in real-world applications. Therefore, ensuring that the training dataset is an aligned sample is essential for developing robust and reliable machine learning models.In conclusion, the term aligned sample is integral to various fields, including medical research, social sciences, and machine learning. It embodies the idea of organizing data in a way that maximizes the validity and reliability of research findings. Whether we are conducting a clinical trial, analyzing survey data, or training a machine learning model, the use of aligned samples allows for more accurate and meaningful insights. As researchers and practitioners continue to emphasize the importance of data integrity, understanding and utilizing aligned samples will remain a cornerstone of effective analysis and decision-making processes.

在研究和数据分析领域，术语aligned sample指的是一组以有效比较和分析的方式组织的数据点。这个概念在实验中尤为重要，因为一致性和准确性至关重要。aligned sample确保所有变量都被控制，从而使研究人员能够从他们的发现中得出有意义的结论。例如，在测试新药的临床试验中，aligned sample可能包括具有相似特征的参与者，如年龄、性别和健康状况。通过对这些样本进行对齐，研究人员可以隔离药物的效果，而不受其他因素的干扰。此外，aligned samples的重要性不仅限于临床研究。在社会科学中，研究人员经常使用aligned samples来研究不同人口统计学中的行为。在分析调查结果时，拥有一个aligned sample有助于确保数据反映特定群体的真实意见，而不是被异常值或无关数据点扭曲。这种对齐在得出准确结论和根据收集的数据做出明智决策中至关重要。此外，在机器学习领域，aligned samples的概念在训练算法中也发挥着重要作用。为了让模型有效学习，它需要在一个准确代表问题空间的aligned sample上进行训练。如果训练数据没有对齐，模型可能会产生偏见或不准确的预测，从而导致在实际应用中的表现不佳。因此，确保训练数据集是aligned sample对于开发稳健和可靠的机器学习模型至关重要。总之，术语aligned sample在医学研究、社会科学和机器学习等多个领域都至关重要。它体现了以最大化研究发现的有效性和可靠性为目标组织数据的理念。无论我们是在进行临床试验、分析调查数据还是训练机器学习模型，使用aligned samples都能带来更准确和有意义的见解。随着研究人员和从业者继续强调数据完整性的重要性，理解和利用aligned samples将始终是有效分析和决策过程的基石。