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Remove redundant code examples

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Aurélien Geron
2021-05-27 15:03:41 +12:00
parent 5d6fec78b5
commit 07bc7aff0a
1 changed files with 0 additions and 51 deletions
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51
01_the_machine_learning_landscape.ipynb
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@@ -750,57 +750,6 @@
"plt.show()" "plt.show()"
] ]
}, },
{
"cell_type": "code",
"execution_count": 37,
"metadata": {},
"outputs": [],
"source": [
"backup = oecd_bli, gdp_per_capita\n",
"\n",
"def prepare_country_stats(oecd_bli, gdp_per_capita):\n",
" return sample_data"
]
},
{
"cell_type": "code",
"execution_count": 38,
"metadata": {},
"outputs": [],
"source": [
"# Replace this linear model:\n",
"import sklearn.linear_model\n",
"model = sklearn.linear_model.LinearRegression()"
]
},
{
"cell_type": "code",
"execution_count": 39,
"metadata": {},
"outputs": [],
"source": [
"# with this k-neighbors regression model:\n",
"import sklearn.neighbors\n",
"model = sklearn.neighbors.KNeighborsRegressor(n_neighbors=3)"
]
},
{
"cell_type": "code",
"execution_count": 40,
"metadata": {},
"outputs": [],
"source": [
"X = np.c_[country_stats[\"GDP per capita\"]]\n",
"y = np.c_[country_stats[\"Life satisfaction\"]]\n",
"\n",
"# Train the model\n",
"model.fit(X, y)\n",
"\n",
"# Make a prediction for Cyprus\n",
"X_new = np.array([[22587.0]]) # Cyprus' GDP per capita\n",
"print(model.predict(X_new)) # outputs [[ 5.76666667]]"
]
},
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": null,