" algorithm = 'fpgrowth', data = df, min_support = min_support)\n",
" algorithm = 'fpgrowth',\n",
" data = df,\n",
" min_support = min_support)\n",
"print(f\"Repeated item sets using FP Growth with min_support = {min_support}:\")\n",
"print(f\"Repeated item sets using FP Growth with min_support = {min_support}:\")\n",
"repeated_item_sets_fpg"
"repeated_item_sets_fpg"
]
]
...
@@ -712,7 +716,7 @@
...
@@ -712,7 +716,7 @@
"cell_type": "markdown",
"cell_type": "markdown",
"metadata": {},
"metadata": {},
"source": [
"source": [
"# ***4. Performance comparison***\n",
"# ***3. Performance comparison***\n",
"[Back to contents](#Contents)"
"[Back to contents](#Contents)"
]
]
},
},
...
@@ -720,7 +724,7 @@
...
@@ -720,7 +724,7 @@
"cell_type": "markdown",
"cell_type": "markdown",
"metadata": {},
"metadata": {},
"source": [
"source": [
"## ***4.1. Load dataset***"
"## ***3.1. Load dataset***"
]
]
},
},
{
{
...
@@ -747,7 +751,7 @@
...
@@ -747,7 +751,7 @@
"cell_type": "markdown",
"cell_type": "markdown",
"metadata": {},
"metadata": {},
"source": [
"source": [
"## ***4.2. Measure time for Apriori***"
"## ***3.2. Measure time for Apriori***"
]
]
},
},
{
{
...
@@ -759,7 +763,7 @@
...
@@ -759,7 +763,7 @@
"name": "stdout",
"name": "stdout",
"output_type": "stream",
"output_type": "stream",
"text": [
"text": [
"Execution time for Apriori: 10.025006294250488 seconds\n"
"Execution time for Apriori: 11.745002031326294 seconds\n"
]
]
}
}
],
],
...
@@ -784,7 +788,7 @@
...
@@ -784,7 +788,7 @@
"cell_type": "markdown",
"cell_type": "markdown",
"metadata": {},
"metadata": {},
"source": [
"source": [
"## ***4.3. Measure time for FP Growth***"
"## ***3.3. Measure time for FP Growth***"
]
]
},
},
{
{
...
@@ -796,7 +800,7 @@
...
@@ -796,7 +800,7 @@
"name": "stdout",
"name": "stdout",
"output_type": "stream",
"output_type": "stream",
"text": [
"text": [
"Execution time for FP Growth: 2.471029281616211 seconds\n"
"Execution time for FP Growth: 2.6620032787323 seconds\n"
]
]
}
}
],
],
...
@@ -821,14 +825,14 @@
...
@@ -821,14 +825,14 @@
"cell_type": "markdown",
"cell_type": "markdown",
"metadata": {},
"metadata": {},
"source": [
"source": [
"## ***4.5. Results***"
"## ***3.4. Results***"
]
]
},
},
{
{
"cell_type": "markdown",
"cell_type": "markdown",
"metadata": {},
"metadata": {},
"source": [
"source": [
"> **As we can notice, `FP Growth` is much faster than `Apriori`** ***(about 4 times faster!)***. \n",
"> **As we can notice, `FP Growth` is much faster than `Apriori`** ***(about 5 times faster!)***. \n",
"> **This is because `FP Growth` requires access the dataset multiple times to find repeated groups, when `Apriori` constructs the tree from the beginning and then don't access dataset again (working only with tree)**"
"> **This is because `FP Growth` requires access the dataset multiple times to find repeated groups, when `Apriori` constructs the tree from the beginning and then don't access dataset again (working only with tree)**"