Valentino Constantinou vc1492a

## Apriori.py
#-*- coding:utf-8 - *-


def load_dataset():
    "Load the sample dataset."
    return [[1, 3, 4], [2, 3, 5], [1, 2, 3, 5], [2, 5]]


def createC1(dataset):
    "Create a list of candidate item sets of size one."

## box-shadow.html
<!DOCTYPE html>
<html>
	<head>
		<title>Box Shadow</title>

		<style>
			.box {
				height: 150px;
				width: 300px;
				margin: 20px;

## gist:1046959
"""
Hilbert matrix using numpy. Contains:

  - hilb(n, m) : returns the Hilbert matrix of size (n, m)

  - invhilb(n) : returns the inverse of the Hilbert matrix of size (n, n)
"""
import numpy as np
from math import factorial
	#-- coding:utf-8 - -


	def load_dataset():
	"Load the sample dataset."
	return [[1, 3, 4], [2, 3, 5], [1, 2, 3, 5], [2, 5]]


	def createC1(dataset):
	"Create a list of candidate item sets of size one."
	<!DOCTYPE html>
	<html>
	<head>
	<title>Box Shadow</title>

	<style>
	.box {
	height: 150px;
	width: 300px;
	margin: 20px;
	"""
	Hilbert matrix using numpy. Contains:

	- hilb(n, m) : returns the Hilbert matrix of size (n, m)

	- invhilb(n) : returns the inverse of the Hilbert matrix of size (n, n)
	"""
	import numpy as np
	from math import factorial