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add params for avoiding warn and improving perf.

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rickiepark
2018-01-30 17:19:37 +09:00
parent 0f46b85009
commit 385d635e92
3 changed files with 8 additions and 8 deletions
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6
03_classification.ipynb
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@@ -241,7 +241,7 @@
"source": [
"from sklearn.linear_model import SGDClassifier\n",
"\n",
"sgd_clf = SGDClassifier(random_state=42)\n",
"sgd_clf = SGDClassifier(max_iter=5, random_state=42)\n",
"sgd_clf.fit(X_train, y_train_5)"
]
},
@@ -766,7 +766,7 @@
"outputs": [],
"source": [
"from sklearn.multiclass import OneVsOneClassifier\n",
"ovo_clf = OneVsOneClassifier(SGDClassifier(random_state=42))\n",
"ovo_clf = OneVsOneClassifier(SGDClassifier(max_iter=5, random_state=42))\n",
"ovo_clf.fit(X_train, y_train)\n",
"ovo_clf.predict([some_digit])"
]
@@ -1185,7 +1185,7 @@
"param_grid = [{'weights': [\"uniform\", \"distance\"], 'n_neighbors': [3, 4, 5]}]\n",
"\n",
"knn_clf = KNeighborsClassifier()\n",
"grid_search = GridSearchCV(knn_clf, param_grid, cv=5, verbose=3)\n",
"grid_search = GridSearchCV(knn_clf, param_grid, cv=5, verbose=3, n_jobs=-1)\n",
"grid_search.fit(X_train, y_train)"
]
},