generalization

generalization的音标是[ˌdʒenərəlaɪˈzeɪʃn]，基本翻译是“一般化，概括化”，速记技巧可以是将其拆分为单词部分进行记忆。

Generalization这个词的词源可以追溯到拉丁语generalis，意为“普遍的”或“一般的”。Generalization通过借词形式演变为英文单词，其变化形式包括名词形式generalization和形容词形式general。

相关单词：

1. General：作为形容词和名词，意为“普遍的”或“一般的”，与generalization有密切关系，因为generalization就是对一般性的归纳或概括。

2. Generalist：一个名词，指具有广泛知识或兴趣的人，通常指在多个领域都有一定了解的人。这个词也反映了generalization的概念，因为generalist是对多个领域的一般性了解。

3. Generalization Error：在机器学习中，泛化错误是指模型未能适应新的、未见过的数据或情境。这个词反映了generalization的概念，即模型应该能够从已知的一般性规律中推断出新的具体情况。

4. Generalization Error Rate：在统计和机器学习中，泛化误差率是指模型在未见过的数据上的错误率。这个词也反映了generalization的概念，因为泛化误差率是模型在未知情况下的表现。

5. Generalization Problem：在机器学习中，泛化问题是指模型在未见过的数据上表现不佳的问题。这个问题通常是由于模型过于简单或过于特殊化导致的，需要使用更复杂的模型或更全面的数据来解决。

以上这些单词都反映了generalization的概念和重要性，即从已知的一般性规律中推断出新的具体情况的能力。这种能力对于机器学习、人工智能和数据分析等领域至关重要。

常用短语：

1. generalize from experience

2. generalize to other cases

3. generalize a concept

4. generalize a theory

5. generalize a hypothesis

6. generalize a rule

7. generalize a principle

双语例句：

1. Based on my experience, I can generalize that this method works well for most cases.

2. We can"t simply generalize from one example to other cases.

3. The theory we developed can be generalized to other similar situations.

4. The hypothesis we tested doesn"t generalize well to other contexts.

5. We need to be careful not to generalize too much when making judgments about people.

6. The rule we observed in one situation may not generalize to other situations.

7. The principle we discovered has broad applications in many fields.

英文小作文：

Generalization is an essential part of scientific research and development, as it allows us to make connections between different ideas and apply them to new situations. Generalizing from previous experience or experiments can help us identify patterns and trends that can be used to develop new theories, hypotheses, and rules. However, generalization is not always straightforward, and it requires careful consideration and testing to ensure that the generalization is valid and applicable in different contexts.

For example, when developing a new product or service, we need to consider how it will be used in different markets and industries. Generalizing from one market or industry may not be applicable in other contexts, as different factors such as consumer preferences, regulations, and competition may vary significantly. Similarly, when developing a new technology or process, we need to consider how it will perform under different conditions and how it will be used by different users. Generalizing from one case or experiment may not be sufficient to fully understand the potential and limitations of the technology or process. Therefore, generalization is an essential part of scientific research and development, but it requires careful consideration and testing to ensure that the generalization is valid and applicable in different contexts.