Evaluates dataset readiness for predictive modeling across four foundational statistical pillars: data quality, data leakage, distribution transformations, and feature stability. Produces an overall Model Readiness score (0-100) and a gatekeeping verdict.
Value
A PrismReport S3 object containing:
- quality
List of data quality metrics returned by
quality_score.- leakage
List of data leakage diagnostics returned by
detect_leakage.- transformation
List of transformation recommendations returned by
recommend_transform.- stability
List of stability metrics returned by
feature_stability.- readiness
Overall composite Model Readiness score (0-100).
- verdict
Gatekeeping verdict:
"Model Ready","Proceed with Caution", or"Action Required".
Details
The four evaluation dimensions include:
Data Quality: Evaluates missingness, duplicate rows, and constant features.
Data Leakage: Identifies identifier keys, duplicate features, high-cardinality columns, and target correlation leakers.
Transformations: Evaluates skewness and excess kurtosis to recommend variance-stabilizing transforms (Box-Cox, Yeo-Johnson, Log).
Feature Stability: Assesses covariate distribution drift via Population Stability Index (PSI) and Wasserstein distance.
Examples
report <- prism(airquality, target = "Ozone")
print(report)
#>
#> =========================================================
#> Prism Report
#> =========================================================
#>
#> Model Readiness : 96.5
#> Overall Verdict : Proceed with Caution
#>
#> =========================================================
#> Data Quality
#> =========================================================
#>
#> Quality Score : 97.6 /100
#> Verdict : Excellent
#>
#> Missing Values : 4.79 %
#> Duplicate Rows : 0
#> Constant Columns : 0
#>
#> ✓ No major data quality issues detected.
#>
#>
#> =========================================================
#> Leakage Detection
#> =========================================================
#>
#> Leakage Safety Score : 100 /100
#> Verdict : Safe
#>
#> Identifier Columns : 0
#> Duplicate Columns : 0
#> High Cardinality : 0
#> Target Leakage : 0
#> Correlation Leakage : 0
#>
#> ✓ No potential leakage detected.
#>
#>
#> =========================================================
#> Transformation Analysis
#> =========================================================
#>
#> Numeric Variables Analysed : 6
#> Transformations Needed : 1
#>
#> Variable Finding Recommendation
#> ----------------------------------------------------------------------
#> Ozone Severely right-skewed Box-Cox
#>
#> ✓ Remaining 5 variables require no transformation.
#>
#> =========================================================
#> Feature Stability
#> =========================================================
#>
#> Overall Stability Score : 43.3 /100
#> Verdict : Drift Warning (Unstable Features Detected)
#>
#> Evaluated Features : 6
#> Stable Features : 0
#> Moderate Drift : 2
#> Unstable Features : 4
#>
#> Unstable Features (Drift Detected)
#> ----------------------------------
#> • Solar.R (PSI: 0.3718)
#> • Wind (PSI: 0.2610)
#> • Temp (PSI: 0.5042)
#> • Month (PSI: 5.0878)
#>
#> Moderate Drift
#> --------------
#> • Ozone (PSI: 0.1814)
#> • Day (PSI: 0.1401)
#>
#>
summary(report)
#>
#> =========================================================
#> Prism Summary
#> =========================================================
#>
#> Model Readiness : 96.5
#> Overall Verdict : Proceed with Caution
#>
#> Data Quality
#> -----------------------------------------
#> Data Quality Score : 97.6/100 (Excellent)
#>
#> Leakage Detection
#> -----------------------------------------
#> Leakage Safety Score : 100/100 (Safe)
#>
#> Transformation Analysis
#> -----------------------------------------
#> 1 variable(s) require transformation.
#>
#> • Ozone -> Box-Cox
#>
#> Feature Stability
#> -----------------------------------------
#> Overall Stability Score : 43.3/100
#> Stability Verdict : Drift Warning (Unstable Features Detected)
#> Stable Features : 0
#> Moderate Drift : 2
#> Unstable Features : 4
#>
#> ⚠ Unstable Features:
#> • Solar.R
#> • Wind
#> • Temp
#> • Month
#>
#> Moderate Drift:
#> • Ozone
#> • Day