spmf-wrapper 0.5.0

Python Wrapper for SPMF

SPMF

Python Wrapper for SPMF Java library.

Information

This module contains python wrappers for pattern mining algorithms implemented in SPMF Java library. Each algorithm is implemented as a standalone Python class with fully descriptive and tested APIs. It also provides native support for Pandas dataframes.

Why? If you're in a Python pipeline, it might be cumbersome to use Java as an intermediate step. Using spmf-wrapper you can stay in your pipeline as though Java is never used at all.

Installation

pip install spmf-wrapper

A Java Runtime Environment is required to run this wrapper. If an existing installation is not detected, JRE v21 is automatically installed using install-jdk python module at $HOME/.jre/jdk-21.0.2+13-jre. If you prefer to install Java Runtime manually, follow instructions here. Test installation by running the following command on the terminal:

> java -version
java version "1.8.0_391"
Java(TM) SE Runtime Environment (build 1.8.0_391-b13)
Java HotSpot(TM) 64-Bit Server VM (build 25.391-b13, mixed mode)

Usage

Example:

from spmf import EMMA

emma = EMMA(min_support=2, max_window=2, timestamp_present=True, transform=True)
output = emma.run_pandas(input_df)

Input:

	Time points	Itemset
0	1	a
1	2	a
2	3	a
3	3	b
4	6	a
5	7	a
6	7	b
7	8	c
8	9	b
9	11	d

Output:

	Frequent episode	Support
0	a	5
1	b	3
2	a b	2
3	a-> a	3
4	a -> b	2
5	a -> a b	2

See examples for more details.

For a detailed explanation of the algorithm and parameters, refer to the corresponding webpage in the SPMF documentation.

Implementation Checklist

Sequential Pattern Mining

Algorithm	Type	Implemented
PrefixSpan	Frequent Sequential Pattern	✓
GSP	Frequent Sequential Pattern
SPADE	Frequent Sequential Pattern	✓
CM-SPADE	Frequent Sequential Pattern	✓
SPAM	Frequent Sequential Pattern	✓
CM-SPAM	Frequent Sequential Pattern
FAST	Frequent Sequential Pattern
LAPIN	Frequent Sequential Pattern
ClaSP	Frequent Closed Sequential Pattern	✓
CM-ClaSP	Frequent Closed Sequential Pattern	✓
CloFAST	Frequent Closed Sequential Pattern
CloSpan	Frequent Closed Sequential Pattern
BIDE+	Frequent Closed Sequential Pattern
Post Processing SPAM or PrefixSpan	Frequent Closed Sequential Pattern
MaxSP	Frequent Maximal Sequential Pattern
VMSP	Frequent Maximal Sequential Pattern	✓
FEAT	Frequent Sequential Generator Pattern
FSGP	Frequent Sequential Generator Pattern
VGEN	Frequent Sequential Generator Pattern	✓
NOSEP	Non-overlapping Sequential Pattern	✓
GoKrimp	Compressing Sequential Pattern
TKS	Top-k Frequent Sequential Pattern	✓
TSP	Top-k Frequent Sequential Pattern

Episode Mining

Algorithm	Type	Implemented
EMMA	Frequent Episode	✓
AFEM	Frequent Episode	✓
MINEPI	Frequent Episode
MINEPI+	Frequent Episode	✓
TKE	Top-k Frequent Episodes	✓
MaxFEM	Maximal Frequent Episodes	✓
POERM	Episode Rules
POERM-ALL	Episode Rules
POERMH	Episode Rules
NONEPI	Episode Rules	✓
TKE-Rules	Episode Rules	✓
AFEM-Rules	Episode Rules	✓
EMMA-Rules	Epsiode Rules	✓
MINEPI+-Rules	Episode Rules
HUE-SPAN	High Utility Episodes
US-SPAN	High Utility Episodes
TUP	Top-K High Utility Episodes

Bibliography

Fournier-Viger, P., Lin, C.W., Gomariz, A., Gueniche, T., Soltani, A., Deng, Z., Lam, H. T. (2016).
The SPMF Open-Source Data Mining Library Version 2.
Proc. 19th European Conference on Principles of Data Mining and Knowledge Discovery (PKDD 2016) Part III, Springer LNCS 9853,  pp. 36-40.