SPMF: A Java Open-Source Pattern Mining Library
Authors: Philippe Fournier-Viger, Antonio Gomariz, Ted Gueniche, Azadeh Soltani, Cheng-Wei Wu, Vincent S. Tseng
JMLR 2014 | Venue PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We present SPMF, an open-source data mining library offering implementations of more than 55 data mining algorithms. ... The website of the project offers several resources such as documentation with examples of how to run each algorithm, a developer s guide, performance comparisons of algorithms, data sets, an active forum, a FAQ and a mailing list. ... Since its first major release in 2010, SPMF has been used in more than 70 research projects in various domains... |
| Researcher Affiliation | Academia | Philippe Fournier-Viger EMAIL Department of Computer Science University of Moncton, Moncton, NB E1A 3E9, Canada Antonio Gomariz EMAIL Department of Information and Communication Engineering University of Murcia, Murcia 30100, Spain Ted Gueniche EMAIL Azadeh Soltani EMAIL Department of Computer Engineering Ferdowsi University of Mashhad, Iran Cheng-Wei Wu EMAIL Vincent S. Tseng EMAIL Department of Computer Science and Information Engineering National Cheng Kung University, Taiwan |
| Pseudocode | No | Running an algorithm is just a few lines of code. One needs to create an instance of the algorithm, specify its parameter(s), input file and an output file path (if the result is to be saved to a file). For example, the following code runs the Apriori algorithm on a file input.txt with its minsup parameter set to 0.4. Algo Apriori a p r i o r i = new Algo Apriori ( ) ; a p r i o r i . run Algorithm ( 0 . 4 , input . txt , output . txt ) ; |
| Open Source Code | Yes | We present SPMF, an open-source data mining library offering implementations of more than 55 data mining algorithms. ... The source code is available under the GNU General Public License, version 3. |
| Open Datasets | Yes | The website also provides a set of more than 40 large real-life data sets that can be used with the algorithms offered in SPMF. ... Input files for the algorithms are text files. The format that is used is the one from frequent pattern mining competitions such as FIMI (Boyardo et al., 2004) and used by researchers in this domain (files where items are represented by integers). |
| Dataset Splits | No | The paper presents SPMF, a data mining library, and describes its algorithms and how to use them. It does not contain specific details about training, validation, or test dataset splits for any experiments conducted within the paper itself. |
| Hardware Specification | No | The only requirement to run SPMF is to have Java 7 or higher installed. The paper does not specify any particular hardware used for running or testing the algorithms within the context of this publication. |
| Software Dependencies | Yes | SPMF is implemented in Java and is cross-platform. The only requirement to run SPMF is to have Java 7 or higher installed. ...there is no dependency on any other software or library. |
| Experiment Setup | No | The paper provides examples of how to run algorithms using the SPMF library, including specifying parameters like 'minsup'. However, it does not describe a specific experimental setup, such as hyperparameter values, model initialization, or training schedules, for any particular research experiment. |