Karmic Analysis - GettingStoned

Revolutionary Karma Tracking

Our advanced machine learning system analyzes your spiritual practice patterns to calculate comprehensive karma scores, enlightenment probability, and personalized insights for your spiritual journey.

🧠 Machine Learning

Advanced algorithms trained on Buddhist texts and spiritual practice patterns

📈 Bayesian Analysis

Probabilistic models calculate your enlightenment probability with mathematical precision

🎯 Personalized Insights

Custom recommendations based on your unique practice patterns and spiritual goals

847

Karma Score

73%

Enlightenment Probability

Day Streak

Mathematical Framework

Our karmic analysis uses sophisticated mathematical models based on Buddhist philosophy and modern machine learning

📊 Karma Score Mathematical Framework

Core Karma Score Formula

$$K = (W_r \times 0.7) + ((1 - B_r) \times 0.3)$$

Where: $W_r$ = White stone ratio, $B_r$ = Black stone ratio

Volume-Adjusted Karma

$$K_v = K \times \frac{\log_{10}(S + 1)}{\log_{10}(S_{max} + 1)}$$

Where: $S$ = Total stones, $S_{max}$ = Maximum stones in system (10,000)

Comprehensive Karma Score

$$K_c = (K_v \times 0.5) + (E \times 0.3) + (C \times 0.2)$$

Where: $E$ = Engagement score, $C$ = Consistency score

🧠 Enlightenment Probability Calculations

Weighted Stone Calculation

$$W_w = (M \times 2.5) + (I \times 2.0) + (Med \times 1.5) + (R \times 1.0)$$

Where: $M$ = Merit stones, $I$ = Insight stones, $Med$ = Meditation stones, $R$ = Regular white stones

Black Stone Weighting

$$W_b = (A \times 0.5) + (U \times 1.0)$$

Where: $A$ = Analyzed black stones, $U$ = Unanalyzed black stones

Final Enlightenment Probability

$$P_e = \frac{W_w}{W_w + W_b}$$

Final probability capped at 95% to maintain humility

Machine Learning Implementation

🎯 Classification Models

Random Forest: Predicts user engagement levels and spiritual progress categories

Logistic Regression: Determines probability of sustained practice

📈 Regression Models

Poisson Regression: Predicts stone generation rates with offset for time active

Ridge/Lasso: Regularized models prevent overfitting with small datasets

🔍 Clustering Analysis

K-means: Identifies user behavior patterns and spiritual practice types

Hierarchical Clustering: Creates user archetypes for personalized recommendations

Comprehensive Analysis Types

📊

Growth Streaks

Track consecutive days of practice with milestone rewards at 7, 30, and 100 days

📈

Progress Summary

Comprehensive overview of your spiritual development with visual indicators

🔥

Current Virtue Streaks

Track ongoing streaks in different spiritual practices and virtues

🎯

Upcoming Growth Milestones

Predictive analytics show your path to next spiritual achievements

📝

Self-Reporting Analysis

Analyze your self-reported spiritual experiences and insights

💎

White Stone Inflation

Track the increasing value and impact of your positive spiritual actions

📊 Karmic Analysis