| Map > Data Science > Predicting the Future > Modeling > Classification > ZeroR | |||||||||||||||||||||||||||||
ZeroR |
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| ZeroR is the simplest classification method which relies on the target and ignores all predictors. ZeroR classifier simply predicts the majority category (class). Although there is no predictability power in ZeroR, it is useful for determining a baseline performance as a benchmark for other classification methods. | |||||||||||||||||||||||||||||
| Algorithm | |||||||||||||||||||||||||||||
| Construct a frequency table for the target and select its most frequent value. | |||||||||||||||||||||||||||||
| Example: | |||||||||||||||||||||||||||||
| "Play Golf = Yes" is the ZeroR model for the following dataset with an accuracy of 0.64. | |||||||||||||||||||||||||||||
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| Predictors Contribution | |||||||||||||||||||||||||||||
| There is nothing to be said about the predictors contribution to the model because ZeroR does not use any of them. | |||||||||||||||||||||||||||||
| Model Evaluation | |||||||||||||||||||||||||||||
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The following confusion matrix shows that ZeroR only predicts the majority class correctly. As mentioned before, ZeroR is only useful for determining a baseline performance for other classification methods. |
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