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Evelynislost · 2022年02月04日

group 2 被移除是因为频率太低吗?

NO.PZ2021083101000014

问题如下:

As an additional part of the text exploration step, Achler conducts a term frequency analysis to identify outliers. Achler summarizes the analysis in Exhibit 2.

Based on Exhibit 2, Achler should exclude from further analysis words in:

选项:

A.

only Group 1

B.

only Group 2

C.

both Group 1 and Group 2

解释:

C is correct.

Achler should remove words that are in both Group 1 and Group 2. Term frequency values range between 0 and 1. Group 1 consists of the highest frequency values (e.g., “the” = 0.04935), and Group 2 consists of the lowest frequency values (e.g., “naval” = 1.0123e–05).

Frequency analysis on the processed text data helps in filtering unnecessary tokens (or features) by quantifying how important tokens are in a sentence and in the corpus as a whole.

The most frequent tokens (Group 1) strain the machine-learning model to choose a decision boundary among the texts as the terms are present across all the texts, which leads to model underfitting.

The least frequent tokens (Group 2) mislead the machine-learning model into classifying texts containing the rare terms into a specific class, which leads to model overfitting. Identifying and removing noise features is critical for text classification applications.

A is incorrect because words in both Group 1 and Group 2 should be removed.

The words with high term frequency value are mostly stop words, present in most sentences. Stop words do not carry a semantic meaning for the purpose of text analyses and ML training, so they do not contribute to differentiating sentiment.

B is incorrect because words in both Group 1 and Group 2 should be removed.

Terms with low term frequency value are mostly rare terms, ones appearing only once or twice in the data. They do not contribute to differentiating sentiment.

考点:Unstructured Data Exploration

group 2 被移除是因为频率太低吗?

1 个答案

星星_品职助教 · 2022年02月04日

同学你好,

对的。即答案解析中针对B选项的解释:“Terms with low term frequency value are mostly rare terms, ones appearing only once or twice in the data. They do not contribute to differentiating sentiment.”

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