uARMSolver - Man Page

uARMSolver – universal Association Rule Mining Solver

Synopsis

uARMSolver [-v|-?] [-sSETUP_FILE|-s SETUP_FILE]

Description

The framework is written fully in C++ and runs on all platforms. It allows users to preprocess their data in a transaction database, to make discretization of data, to search for association rules and to guide a presentation/visualization of the best rules found using external tools. As opposed to the existing software packages or frameworks, this also supports numerical and real-valued types of attributes besides the categorical ones. Mining the association rules is defined as an optimization and solved using the nature-inspired algorithms that can be incorporated easily. Because the algorithms normally discover a huge amount of association rules, the framework enables a modular inclusion of so-called visual guiders for extracting the knowledge hidden in data, and visualize these using external tools.

Options

-h-?

Show a help message and exit.

-sSETUP_FILE, -s SETUP_FILE

Path to a setup file (default arm.set). See the Files section for details.

Files

This section describes how to describes how to configure a universal ARM Solver (uARMSolver) using a setup file. See also the -s option. The setup file consists of three sections, including:

Lines starting with the % character are comments and are not checked for syntax.

Problem Definition

The problem definition begins with the reserved word Problem, then curly brackets enclosing a series of parameter definitions. Each parameter definition is a line of the form:

parameter = value

The following parameters are supported:

Tdbase_name = file_name

path of the transaction database

Rule_name = file_name

path of an existing archive of mined association rules

Out_name = file_name

path where the archive of mined association rules will be written

Period = integer_value

how many periods are captured by archive files

The Period parameter determines whether more transaction databases or archive files are processed by the solver simultaneously. When its value is more than one, the solver expects that files are named with extensions according to their sequence numbers, e.g., is denotes as a sequence number (e.g., .1, .2, ..., .k. When the Period is set to one, a single input file representing the transaction database or ARM archive is processed.

Algorithm Selection

A line of the form:

Algorithm = mnemonic

selects a particular ARM solver algorithm. For example, the Differential Algorithm has mnemonic DE, Particle Swarm Optimization has mnemonic PSO, and so on.

When the algorithm is NONE, the solver does not perform optimization. Instead, it expects an ARM archive produced by another traditional algorithm (such as Apriori) and focuses on the visualization section of the process.

Algorithm-Specific Parameters

Next are algorithm-specific parameter blocks. These begin with a line of the form

mnemonic_PARAM

followed by curly brackets enclosing a series of parameter definitions of the form

mnemonic_param = value

For example, the Differential Algorithm (DE) supports the following parameters:

DE_NP = integer_value

population size of DE algorithm

DE_FES = integer_value

maximum number of fitness function evaluations

DE_RUNS = integer_value

maximum number of an independent DE runs

DE_F = float_value

scaling factor used by DE mutation strategy

DE_CR = float_value

crossover parameter controlling the DE mutation strategy

DE_STRATEGY = integer_value in [1,12]

specific DE mutation strategy

Visualization Selection

In the future, the solver will support a visualization method. A line of the form:

Visualization = mnemonic

selects a particular method of preparing the data from the ARM archive for visualization.

Two algorithms are planned:

FLOW

River flow

METRO

Metro map

Method NONE will disable visualization preparation.

Visualization Parameters

Visualization methods will have method-specific parameter blocks similar to the algorithm-specific parameter blocks for the ARM solver.

Examples

uARMSolver -s arm.set

Info

Novermber 2021