Empirical Study of Marriage Muhurtam Decision Processes through Astrological Data

The rapid expansion of data and the evolution of analytical technologies have
positioned data-driven methodologies as indispensable tools for extracting meaningful
insights across diverse disciplines. Established techniques such as hypothesis testing,
exploratory data analysis and predictive modeling are increasingly employed to address
complex organizational and societal challenges. Astrology is one such domain, which
requires exploration of insights with clearly specified standards. Data presentation in media
on Astrology is looking like just illusion, but not like an illustration. The current study
bridges the gap by investigating an astrological dataset comprising multiple relevant
parameters to examine decision-making processes that are associated with marriage
Muhurtam (auspicious timing). This work contributes to bridging traditional cultural
practices with modern computational analytics, offering a distinctive perspective on the
intersection of data science and astrology.
Using a novel algorithm, AstroClassifier, the researchers are trying to outstate the
reality behind the decision-making. To fulfill the gap of understanding on Astrology, the
algorithm uses three analytical approaches and the combination of these methods enhance the
accuracy of predicting marriage Muhurtam decisions. Comparative assessments against
existing models demonstrate the superior performance of the proposed approach. The
findings underscore the potential of integrating automated decision-support systems with
transparent explanations of astrological principles, thereby reinforcing the credibility of
astrology in contemporary contexts.