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Yash Vasudevayash@analysis.hub
YV

Cross-Report Analytics Hub

Comparative model performance, statistical variance, and trend correlations across published reports.

Machine Learning Model Performance Comparison
Goodness of fit (R² Score) & Test Error across trained models
Category Focus & Report Distribution
Proportion of published analytical domains
Macro Trends Overlay: Annual Inflation vs Delhi Rainfall (2018–2025)
Comparing annual CPI YoY growth (%) against annual cumulative rainfall (mm)
Cross-Report Methodology & Benchmark Matrix
Performance metrics for ML trained models and domain statistics for exploratory studies
Report Title Domain Methodology / Algorithm Sample Size Model Metrics (R² / MAE) Primary Report Metric Status
Judicial & Social Dynamics
Public crime data reveals a 49.6% cumulative expansion in IPC crimes alongside an 85.1% trial backlog in courts, emphasizing systemic delays in justice delivery.
Seasonality & Economic Synchronization
Food inflation spikes in the CPI report closely track monsoon fluctuations, while spatial crime concentration highlights regional enforcement priorities.
Sports Performance & Franchise Risk
IPL analysis reveals severe franchise vulnerability when single-player run dependence exceeds 28% (e.g. RR 2019 at 31.9% and RCB 2023 at 31.4%), while trajectory modeling quantifies meteor arcs vs volume accumulators.
Predictive Maintenance & Sensor Degradation
NASA C-MAPSS turbofan analysis shows sensor_11 as the strongest RUL predictor (|Pearson|=0.696). XGBoost with 282 temporal features achieves test MAE of 10.37 cycles and NASA PHM score of 309.72, outperforming the Random Forest baseline by 12.1% on asymmetric scoring.