Research map / Learning theory and algorithms / Prediction and decision losses
Categorical Neighbour Correlation Coefficient (CnCor) for Detecting Relationships between Categorical Variables
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use CnCor instead of nCor for categorical targets | Association detection on categorical data · Synthetic E1–E5 | association detection power | Helped |
| Use CnCor instead of the baseline association measures | Association detection on categorical data · Synthetic E1–E5 | association detection power | Helped |
| Use CnCor-based COE-BES for backward feature elimination | Feature selection · Six synthetic datasets | k0 | Helped |
| Use CnCor-based COE-BES instead of the baseline feature-selection methods | Feature selection with k-NN and AdaBoost evaluation · Nine benchmark datasets | classification accuracy | Helped |
| Use randomly or unfavorably assigned category labels rather than ordinal labels | CnCor · Synthetic association detection | association detection robustness | No clear effect |
| Use randomly or unfavorably assigned category labels rather than ordinal labels | nCor · Synthetic association detection | association detection power | Hurt |
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