Dataset: potions
Round ID: 280
Prompt used:
Classification Rules for Entity Effectiveness:
1. High Effectiveness Criteria:
- FizzIntensity must be > 45
- ColourShift must be > 10
2. Low Effectiveness Criteria:
- FizzIntensity must be < 40
- ColourShift must be < 10
3. Borderline Case Scoring:
- Calculate a weighted score:
(FizzIntensity * 0.6) + (ColourShift * 0.4)
- If score > 35, classify as Effective
- If score < 30, classify as Ineffective
4. Intermediate Cases:
- If criteria are not clearly met, use the weighted score to determine classification
- Carefully evaluate cases with FizzIntensity between 40-45 and ColourShift between 10-15
Classification Decision Process:
- First check high and low effectiveness criteria
- If inconclusive, apply weighted scoring
- Aim to minimize false positives and false negatives by using a nuanced approach
Confusion Matrix:
Predicted Effective Predicted Ineffective
Actual Effective 4 5
Actual Ineffective 1 10
Accuracy: 0.700
Precision: 0.800
Recall: 0.444
F1 Score: 0.571
Examples for Correctly predicted Effective: (Correct answer: Effective, What the previous set of rules predicted: Effective)
Entity Data:
FizzIntensity: 44.953373
ColourShift: 12.993897
Examples for Falsely predicted Ineffective when it should have been Effective: (Correct answer: Effective, What the previous set of rules predicted: Ineffective)
Entity Data:
FizzIntensity: 37.055344
ColourShift: 15.48838
Examples for Falsely predicted Effective when it should have been Ineffective: (Correct answer: Ineffective, What the previous set of rules predicted: Effective)
Entity Data:
FizzIntensity: 49.864723
ColourShift: 16.120462
Examples for Correctly predicted Ineffective: (Correct answer: Ineffective, What the previous set of rules predicted: Ineffective)
Entity Data:
FizzIntensity: 31.36187
ColourShift: 13.327494
Round ID: 347
Prompt used:
To classify the outcomes of the dataset entities based on FizzIntensity and ColourShift, use the following rules:
1. Predict 'Effective' if FizzIntensity is greater than or equal to 45; prioritize these entities for effective predictions.
2. Predict 'Ineffective' if FizzIntensity is less than 35, regardless of ColourShift.
3. For FizzIntensity between 35 and 45, consider:
- Predict 'Effective' if ColourShift is greater than or equal to 13 and less than or equal to 20.
- Predict 'Effective' if ColourShift is above 15 and FizzIntensity is closer to 45.
- Predict 'Ineffective' if ColourShift is below 10, emphasizing the low value as ineffective.
4. If FizzIntensity is less than 40 and ColourShift is between 10 and 13, predict 'Ineffective'.
These rules aim to decrease both false positives and false negatives in predictions by setting clear thresholds and decision criteria based on patterns from past data and adding considerations for borderline ColourShift values.
Confusion Matrix:
Predicted Effective Predicted Ineffective
Actual Effective 6 3
Actual Ineffective 5 6
Accuracy: 0.600
Precision: 0.545
Recall: 0.667
F1 Score: 0.600
Examples for Correctly predicted Effective: (Correct answer: Effective, What the previous set of rules predicted: Effective)
Entity Data:
FizzIntensity: 45.78967
ColourShift: 12.371225
Examples for Falsely predicted Ineffective when it should have been Effective: (Correct answer: Effective, What the previous set of rules predicted: Ineffective)
Entity Data:
FizzIntensity: 42.094933
ColourShift: 12.042143
Examples for Falsely predicted Effective when it should have been Ineffective: (Correct answer: Ineffective, What the previous set of rules predicted: Effective)
Entity Data:
FizzIntensity: 40.698505
ColourShift: 14.4273
Examples for Correctly predicted Ineffective: (Correct answer: Ineffective, What the previous set of rules predicted: Ineffective)
Entity Data:
FizzIntensity: 31.36187
ColourShift: 13.327494
Round ID: 486
Prompt used:
Prompt: If FizzIntensity is greater than 40, predict as Effective. If FizzIntensity is 40 or lower, predict as Ineffective.
Confusion Matrix:
Predicted Effective Predicted Ineffective
Actual Effective 7 2
Actual Ineffective 3 8
Accuracy: 0.750
Precision: 0.700
Recall: 0.778
F1 Score: 0.737
Examples for Correctly predicted Effective: (Correct answer: Effective, What the previous set of rules predicted: Effective)
Entity Data:
FizzIntensity: 42.094933
ColourShift: 12.042143
Examples for Falsely predicted Ineffective when it should have been Effective: (Correct answer: Effective, What the previous set of rules predicted: Ineffective)
Entity Data:
FizzIntensity: 37.055344
ColourShift: 15.48838
Examples for Falsely predicted Effective when it should have been Ineffective: (Correct answer: Ineffective, What the previous set of rules predicted: Effective)
Entity Data:
FizzIntensity: 40.698505
ColourShift: 14.4273
Examples for Correctly predicted Ineffective: (Correct answer: Ineffective, What the previous set of rules predicted: Ineffective)
Entity Data:
FizzIntensity: 28.113564
ColourShift: 20.790554
| Predicted + | Predicted - | |
|---|---|---|
| Actual + | 6 | 3 |
| Actual - | 3 | 8 |
Accuracy 0.700, Precision 0.667, Recall 0.667, F1 0.667