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AnnaZ · 2023年01月13日

这个知识点23年删掉了?

NO.PZ2021083101000004

问题如下:

Bector then computes TF–IDF (term frequency–inverse document frequency) for several words in the collection and tells Azarov the following:

    Statement 1 IDF is equal to the inverse of the document frequency measure.

    Statement 2 TF at the collection level is multiplied by IDF to calculate TF–IDF.

    Statement 3 TF–IDF values vary by the number of documents in the dataset, and therefore, model performance can vary when applied to a dataset with just a few documents.

    Which of Bector’s statements regarding TF, IDF, and TF–IDF is correct?

    选项:

    A.

    Statement 1

    B.

    Statement 2

    C.

    Statement 3

    解释:

    C is correct.

    Statement 3 is correct. TF–IDF values vary by the number of documents in the dataset, and therefore, the model performance can vary when applied to a dataset with just a few documents.

    A is incorrect because IDF is calculated as the log of the inverse, or reciprocal, of the document frequency (DF) measure.

    B is incorrect because TF at the sentence (not collection) level is multiplied by IDF to calculate TF–IDF.

    考点:Unstructured Data Exploration - Feature Selection - Different TF measures

    这个知识点是不是23年考纲里面删掉了

    1 个答案

    星星_品职助教 · 2023年01月13日

    同学你好,

    仍在考纲内,参照讲义中这个部分的内容。

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