  This paper describes the validation of a new background discrimination method
based on Random Forest technique by re-analysing the Markarian 421 (Mrk 421)
observations performed by the TACTIC (TeV Atmospheric Cherenkov Telescope with
Imaging Camera) gamma-ray telescope. The Random Forest technique is a flexible
multivariate method which combines Bagging and Random Split Selection to
construct a large collection of decision trees and then combines them to
construct a common classifier. Markarian 421 in a high state was observed by
TACTIC during December 07, 2005 - April 30, 2006 for 202 h. Previous analysis
of this data led to a detection of flaring activity from the source at Energy $
>$ 1 TeV. Within this data set, a spell of 97 h revealed strong detection of a
gamma-ray signal with daily flux of > 1 Crab unit on several days. Here we
re-analyze this spell as well as the data from the entire observation period
with the Random Forest method. Application of this method led to an improvement
in the signal detection strength by $\sim 26\%$ along with a $\sim 18\%$
increase in detected $\gamma$ rays compared to the conventional Dynamic
Supercuts method. The resultant differential spectrum obtained is represented
by a power law with an exponential cut off $\Gamma = -2.51 \pm 0.10$ and $E_{0}
= 4.71 \pm 2.20$ TeV. Such a spectrum is consistent with previously reported
results and justifies the use of Random Forest method for analyzing data from
atmospheric Cherenkov telescopes.
