NO.PZ202208300200000603
问题如下：
Khan’s idea for the conversion of the选项：
A.term frequency. B.one hot encoding. C.name entity recognition.解释：
SolutionB is correct. The process of decomposing a single categorical feature with multiple values, in this case denoted by the multiple types of precipitation, into individual features by type (e.g., is_drizzle, is_rain, is_snow), and recording the results in binary form (0 or 1) is called one hot encoding.
A is incorrect. Term frequency is a form of basic text statistics that determines the ratio of the number of times a given word (token) occurs in all the texts in the dataset relative to the total number of tokens in the dataset.
C is incorrect. Name entity recognition is a process when using an existing library or package that can be applied in many programming languages to analyze the individual tokens and their surrounding semantics to tag an object class to the token, such as organization, location, and date.
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