semvec/pypi-packages huggingface dataset:
LPatternIdentification 0.0.1
Identify a set of L patterns from a binary class dataset
Requires Python: >=3.6

# LPatternIdentification

The formal mathematical definition of the l-Pattern Identification Problem is as follows:

## Input:

A finite alphabet Σ, two disjoint sets Good, Bad ⊆ Σn of strings and an integer l > 0

## Problem question:

Is there a set of P patterns such that: |P| ≤ l and P → (Good, Bad)?


## 1. Install:

'''
pip install LPatternIdentification
'''

## 2. Load:

'''
from LPatternIdentification import feature_set, split_data, get_patterns_from_feature_set, reduce_pattern_set
'''

## 3. Prepare data:

Sort dataset by class labels

Separate observations into numpy ndarray

Separate labels into list

## 4. Find set of features

'''
features = feature_set(observations, labels)
'''

## 5. Split observations by classes 

Here, classes are named 'Good' and 'Bad', the 'Good' class being the class of our interest.

'''
split_point, Good, Bad  = split_data(elections_X, elections_y)
'''

## 6. Return a set of patterns that contain the features and are Good

'''
Patterns = get_patterns_from_feature_set(Good, elections_feature_set)
'''

## 7. Identify 'L' number of patterns such that all patterns are uniquely Good and not similar to Bad patterns

'''
Patterns_identified = reduce_pattern_set(Patterns, Bad, 7)
'''