fimproject 0.0.7

Frequent Itemset Mining and Frequent Sequence Mining Algorithms package for ARM

FIMProject - Frequent Itemset Algorithms and Frequent Sequence Mining Algorithms in Python

Installation

FIMProject requires Python 3.7 or newer, and the easiest way to install it is via pip:

pip install FIMProject

Simple Example

from FIM import apriori
from FIM import association_rules
from FIM.utils import TransactionEncoder


# The apriori function expects data in a one-hot encoded pandas DataFrame.
# Suppose we have the following transaction data:
data = [['onion', 'beer', 'crisps', 'beef'],
        ['beer', 'tomato', 'crisps', 'eggs'],
        ['onion', 'crisps', 'eggs'],
        ['beer', 'eggs', 'beef'],
        ['onion', 'beer', 'carrot', 'crisps'],
        ['onion', 'eggs', 'beef'],
        ['onion', 'beer', 'carrot', 'crisps', 'eggs', 'beef'],
        ['onion', 'beer', 'crisps', 'eggs'],
        ['beer', 'tomato', 'carrot', 'eggs'],
        ['onion', 'crisps', 'eggs', 'beef'],
        ['beer', 'carrot', 'crisps', 'eggs']]

# We can transform it into the right format via the TransactionEncoder as follows:
te = TransactionEncoder()
df = te.fit_transform(data, set_pandas=True)

# Now, let us return the items and itemsets with at least 30% support:
freq_items = apriori(df, min_support=0.3)
# Now, let us return the association rules with freq_items df:
rules = association_rules(freq_items, metric="confidince", min_threshold=0.7)

What is df?

df is a pandas dataframe. It is a table of transactions. Each row is a transaction and each column is an item. The value of each cell is the number of items in the transaction.