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> Data Science > Predicting the Future >
Modeling >
Classification > ZeroR |
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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. |
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Algorithm |
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Construct a frequency table for the
target and select its most frequent value. |
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Example: |
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"Play Golf = Yes" is the ZeroR model
for the following dataset with an accuracy of 0.64. |
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Predictors Contribution |
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There is nothing to be said about the
predictors contribution to the model because ZeroR does not use any of
them. |
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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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