Which indicators are used for model evaluation in classification? (Select all that apply)

Question

BlackTom AI · Accepted Answer

Question focus: identifying evaluation metrics used for classification models. We evaluate each option to see whether it serves as a performance indicator in classification tasks.
Option: PCA
- PCA stands for Principal Component Analysis and is primarily a dimensionality reduction technique used for data preprocessing, visualization, or to reduce feature space. It is not an evaluation metric, so it does not measure how well a classifier performs. Therefore, this option is not appropriate as an evaluation indicator for classification.
Option: Precision
- Precision measures the proportion of correctly predicted positive instances among all instances predicted as positive. It directly reflects a classifier’s accuracy on its positive predictions and is a standard evaluation metric in classification, especially when the cost of false positives is high. This is a valid evaluation indicator for classification.
Option: Recall
- Recall (also called sensitivity or true positive rate) assesses the proportion of actual positives that were correctly identified by the model. It complements precision by focusing on the model’s ability to capture positive cases, and is a standard metric in classification problems, particularly when missing positive cases is costly. This is a valid evaluation indicator for classification.
Option: R-squared
- R-squared is a metric used in regression to describe the proportion of variance in the dependent variable explained by the model. It is not appropriate for evaluating classification models, since classification predicts discrete labels rather than continuous values. Therefore, this option is not an evaluation indicator for classification.
Summary: Among the options, PCA and R-squared are not typical classification evaluation metrics, whereas Precision and Recall are standard and appropriate indicators used to evaluate classification performance.

Which indicators are used for model evaluation in classification? (Select all that apply)

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