Wykład 6. Problem nadmiernego dopasowania

This commit is contained in:
Paweł Skórzewski 2022-11-24 07:22:33 +01:00
parent ff0bda56cf
commit eacef8109a
12 changed files with 6330 additions and 51 deletions

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@ -199,18 +199,6 @@
"Jak widać powyżej, tutaj oprócz liczb pojawiają się pewne tekstowe wartości specjalne, takie jak `parter`, `poddasze` czy `niski parter`."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Takie wartości należy zamienić na liczby. Jak?\n",
"* Wydaje się, że `parter` czy `niski parter` można z powodzeniem potraktować jako piętro „zerowe” i zamienić na `0`.\n",
"* Z poddaszem sytuacja nie jest już tak oczywista. Czy mają Państwo jakieś propozycje?\n",
" * Może zamienić `poddasze` na wartość NaN (zobacz poniżej)?\n",
" * Może wykorzystać w tym celu wartość z sąsiedniej kolumny *Liczba pięter w budynku*?\n",
" * Może w ogóle odrzucić przykłady, w których występuje ta wartość? (jeżeli tych przykładów jest bardzo mało)"
]
},
{
"cell_type": "code",
"execution_count": 8,
@ -251,6 +239,18 @@
"alldata[\"Piętro\"].value_counts()\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Takie wartości należy zamienić na liczby. Jak?\n",
"* Wydaje się, że `parter` czy `niski parter` można z powodzeniem potraktować jako piętro „zerowe” i zamienić na `0`.\n",
"* Z poddaszem sytuacja nie jest już tak oczywista. Czy mają Państwo jakieś propozycje?\n",
" * Może zamienić `poddasze` na wartość NaN (zobacz poniżej)?\n",
" * Może wykorzystać w tym celu wartość z sąsiedniej kolumny *Liczba pięter w budynku*?\n",
" * Skoro `poddasze` pojawia się tylko w nielicznych przykładach, może w ogóle odrzucić te przykłady?"
]
},
{
"cell_type": "markdown",
"metadata": {},

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@ -98,7 +98,6 @@
"data = preprocess(data) # wstępne przetworzenie danych\n",
"\n",
"# Podział danych na zbiory uczący i testowy\n",
"split_point = int(0.8 * len(data))\n",
"data_train, data_test = train_test_split(data, test_size=0.2)\n",
"\n",
"# Uczenie modelu\n",
@ -252,7 +251,6 @@
")\n",
"\n",
"# Podział danych na zbiór uczący i zbiór testowy\n",
"split_point = int(0.8 * len(data_iris))\n",
"data_train, data_test = train_test_split(data_iris, test_size=0.2)\n",
"\n",
"# Uczenie modelu\n",
@ -283,7 +281,7 @@
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"display_name": "Python 3.10.6 64-bit",
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
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