Subjective
In Data Science, subjective refers to the opinions, feelings, and biases of individuals that may influence the interpretation and analysis of data. Subjectivity can arise in various stages of the data science process, including data collection, preprocessing, modeling, and evaluation. For example, subjective decisions may be made when selecting which variables to include in a model, how to preprocess the data, or how to evaluate the performance of a model. Subjectivity can also arise when interpreting the results of a model, as different individuals may have different interpretations of the same output. It is important for data scientists to be aware of their own biases and to strive for objectivity in their analysis and decision-making.
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