niaarm.1

.TH NIAARM "1" "October 2022" "" "User Commands"
.SH NAME
.B niaarm
\(en perform Association Rule Mining, output mined rules as csv, get mined rules\(cq statistics
.SH SYNOPSIS
.B niaarm
.RB [ \-h ]
.RB [ \-v ]
.B \-i\ \fIINPUT_FILE
.RB [ \-o\ \fIOUTPUT_FILE ]
.B \-a\ \fIALGORITHM
.RB [ \-s\ \fISEED ]
.RB [ \-\-max\-evals\ \fIMAX_EVALS ]
.RB [ \-\-max\-iters\ \fIMAX_ITERS ]
.B \-\-metrics\ \fIMETRICS\fR\ [\fIMETRICS\fR\ ...]
.RB [ \-\-weights\ \fIWEIGHTS\fR\ [\fIWEIGHTS \ ...]]
.RB [ \-\-log ]
.RB [ \-\-stats ]
.SH OPTIONS
.TP
.B \-h\fR, \fB\-\-help
Show a help message and exit
.TP
.B \-v\fR, \fB\-\-verbose
Show program\(cqs version number and exit
.TP
.B \-i\ \fIINPUT_FILE\fR, \fB\-\-input\-file\ \fIINPUT_FILE
Input file containing a csv dataset
.TP
.B \-o\ \fIOUTPUT_FILE\fR, \fB\-\-output\-file\ \fIOUTPUT_FILE
Output file for mined rules
.TP
.B \-a\ \fIALGORITHM\fR, \fB\-\-algorithm\ \fIALGORITHM
Algorithm to use (niapy class name, e.g. \fBDifferentialEvolution\fR)
.TP
.B \-s\ \fISEED\fR, \fB\-\-seed\ \fISEED
Seed for the algorithm\(cqs random number generator
.TP
.B \-\-max\-evals\ \fIMAX_EVALS
Maximum number of fitness function evaluations
.TP
.B \-\-max\-iters\ \fIMAX_ITERS
Maximum number of iterations
.TP
.B \-\-metrics\ \fIMETRICS\fR\ [\fIMETRICS\fR\ ...]
Metrics to use in the fitness function.
.TP
.B \-\-weights\ \fIWEIGHTS\fR\ [\fIWEIGHTS\fR\ ...]
Weights in range
.B [0,\ 1]
corresponding to
.B \-\-metrics
.TP
.B \-\-log
Enable logging of fitness improvements
.TP
.B \-\-stats
Display stats about mined rules