Merge changes

This commit is contained in:
augustin64 2025-04-01 09:30:28 +02:00
parent 8481103e4d
commit ada69748ce

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@ -335,6 +335,17 @@
" return df.copy()"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "fda6aaad-7b1e-4daa-8d28-cd049df9cec2",
"metadata": {},
"outputs": [],
"source": [
"data_features=filter_df(data)\n",
"data_features"
]
},
{
"cell_type": "markdown",
"id": "d1eb67d7-d16b-4b93-8486-582830ac3903",
@ -407,9 +418,11 @@
]
},
{
"cell_type": "markdown",
"id": "48cbb634-6754-4956-a945-539d329812ef",
"cell_type": "code",
"execution_count": null,
"id": "24e7ff6e-c308-4cc8-aeac-eeb372f4c479",
"metadata": {},
"outputs": [],
"source": [
"In this part, we achieved to do two things for the classification: create a decision tree on the database and, given a cheese and its characteristics, find where it originates from. \n",
"\n"
@ -507,8 +520,27 @@
"metadata": {},
"source": [
"Not good, even quite bad. \n",
"We cannot find the region a cheese originates from given its characteristic. \n",
"\n",
"In short, it seems that we cannot find the region a cheese originates from given its characteristic. "
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "7fd507d0-1a68-4cd7-a12e-12c9ab1061e3",
"metadata": {},
"outputs": [],
"source": [
"model.predict(X)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "9faf2aee-84f5-4633-b3de-039af42d31d3",
"metadata": {},
"outputs": [],
"source": [
"yprime=pd.DataFrame(model.predict(X),columns=[\"latitude\",\"longitude\"])\n",
"\n"
]
},
@ -578,9 +610,11 @@
]
},
{
"cell_type": "markdown",
"id": "84bf779a-36d0-4aa2-b3a2-0da9bb25fc01",
"cell_type": "code",
"execution_count": null,
"id": "78ef08e7-1436-440f-b035-8b480af1cc7b",
"metadata": {},
"outputs": [],
"source": [
"For Pattern Mining, we only kept relevant columns (binary attributes) thus dropping RGB colors and any location based information, keeping only information relevant to the final cheese itself.\n",
"\n",
@ -588,24 +622,6 @@
"\n",
"Est-ce que les fromages artisanaux ont souvent plus de \"goûts\" que les autres ?\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "ce4db7c9-8049-4838-af30-b9fe2bca2925",
"metadata": {},
"outputs": [],
"source": [
"len(data_features[data_features[\"pecorino\"] == True]), len(data_features[data_features[\"pecorino\"] == False])"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "7d9f17c2-6c42-4f24-b0d0-e8640a661801",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {