  We present a python-based program for phenomenological investigations in
particle physics using machine learning algorithms, called \verb"MLAnalysis".
The program is able to convert LHE and LHCO files generated by
\verb"MadGraph5_aMC@NLO" into data sets for machine learning algorithms, which
can analyze the information of the events. At present, it contains three
machine learning (ML) algorithms: isolation forest (IF) algorithm, nested
isolation forest (NIF) algorithm, kmeans anomaly detection (KMAD), and some
basic functionality to analyze the kinematic features of a data set. Users can
use this program to improve the efficiency of searching for new physics
signals.
