稀疏化的英文

Sparseization

怎么读（音标）

/speərzaɪˈzeɪʃ(ə)n/

用法

稀疏化是指将密集的数据或信息转换为稀疏的形式，以便更高效地存储和处理。在计算机科学中，稀疏化被广泛应用于数据压缩、图像处理、机器学习等领域。

例句1-5句且中英对照

1. The sparseization of the image data significantly reduced the storage space needed. (图像数据的稀疏化显著减少了所需的存储空间。)

2. Sparseization techniques have greatly improved the performance of machine learning algorithms. (稀疏化技术极大地提高了机器学习算法的性能。)

3. The sparseization process can help to identify patterns in large datasets more efficiently. (稀疏化过程可以更有效地识别大型数据集中的模式。)

4. By applying sparseization, we were able to reduce the time needed for data processing by half. (通过应用稀疏化，我们成功将数据处理时间缩减了一半。)

5. The goal of sparseization is to simplify and optimize complex data structures for better performance and efficiency. (稀疏化的目标是简化和优化复杂的数据结构，以提高性能和效率。)

同义词及用法

1. Sparsification: This term is often used interchangeably with sparseization and refers to the process of converting dense data into sparse form.

2. Reduction: Similar to sparseization, reduction involves reducing the amount of information or data to make it more manageable.

3. Pruning: This refers to the process of removing unnecessary or irrelevant data from a dataset, resulting in a sparser representation.

4. Thinning: Thinning is a technique used in image processing to reduce the number of pixels in an image while preserving its essential features.

5. Compression: This term is commonly used in data storage and refers to the process of reducing the size of data by eliminating redundant information.

编辑总结

稀疏化是一种重要的数据处理技术，它可以帮助我们更有效地存储和处理大量的数据。通过将密集的数据转换为稀疏形式，我们可以节省存储空间、提高算法性能，并更快地识别数据中的模式。除了在计算机科学中广泛应用外，稀疏化还在其他领域如图像处理、自然语言处理等方面发挥着重要作用。因此，对于网络词典编辑人员来说，了解稀疏化的概念和用法是非常有益的。希望本文能够为您提供有价值的信息，并帮助您更好地理解这一重要概念。