在数据分析的世界里，数据标准化是不可或缺的一环。它能帮助我们更高效地处理数据，提升模型精度。常见的标准化方法之一就是 xi-min(xj) 方法。这种方法通过计算每个数据点与最小值的差值来实现数据归一化，让数据分布更加均匀，便于后续分析。

>Data preprocessing is crucial for accurate analysis. The xi-min(xj) method normalizes data by subtracting the minimum value from each data point, ensuring all values fall within a specific range. This process is especially useful when dealing with datasets that have varying scales or units. By applying this method, we can eliminate the influence of extreme values and focus on the relative differences between data points. Whether you're working on machine learning models, statistical analyses, or visualization tasks, proper data standardization enhances the reliability and accuracy of your results. 🌟✨