![\"Open](\"https://colab.research.google.com/assets/colab-badge.svg\"){kind=icon}
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" ![](\"https://kaggle.com/static/images/open-in-kaggle.svg\")
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" | \n",
" \n",
" | \n",
" \n",
" \n",
" | \n",
"
Pipeline(steps=[('standardscaler', StandardScaler()),\n",
" ('linearsvc', LinearSVC(C=1, random_state=42))])In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. | \n", " | \n",
" \n",
" copy\n",
" copy: bool, default=True If False, try to avoid a copy and do inplace scaling instead. This is not guaranteed to always work inplace; e.g. if the data is not a NumPy array or scipy.sparse CSR matrix, a copy may still be returned.\n", " \n", " | \n",
" True | \n", "
| \n", " | \n",
" \n",
" with_mean\n",
" with_mean: bool, default=True If True, center the data before scaling. This does not work (and will raise an exception) when attempted on sparse matrices, because centering them entails building a dense matrix which in common use cases is likely to be too large to fit in memory.\n", " \n", " | \n",
" True | \n", "
| \n", " | \n",
" \n",
" with_std\n",
" with_std: bool, default=True If True, scale the data to unit variance (or equivalently, unit standard deviation).\n", " \n", " | \n",
" True | \n", "
Pipeline(steps=[('polynomialfeatures', PolynomialFeatures(degree=3)),\n",
" ('standardscaler', StandardScaler()),\n",
" ('linearsvc',\n",
" LinearSVC(C=10, max_iter=10000, random_state=42))])In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. | \n", " | \n",
" \n",
" copy\n",
" copy: bool, default=True If False, try to avoid a copy and do inplace scaling instead. This is not guaranteed to always work inplace; e.g. if the data is not a NumPy array or scipy.sparse CSR matrix, a copy may still be returned.\n", " \n", " | \n",
" True | \n", "
| \n", " | \n",
" \n",
" with_mean\n",
" with_mean: bool, default=True If True, center the data before scaling. This does not work (and will raise an exception) when attempted on sparse matrices, because centering them entails building a dense matrix which in common use cases is likely to be too large to fit in memory.\n", " \n", " | \n",
" True | \n", "
| \n", " | \n",
" \n",
" with_std\n",
" with_std: bool, default=True If True, scale the data to unit variance (or equivalently, unit standard deviation).\n", " \n", " | \n",
" True | \n", "
Pipeline(steps=[('standardscaler', StandardScaler()),\n",
" ('svc', SVC(C=5, coef0=1, kernel='poly'))])In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. | \n", " | \n",
" \n",
" copy\n",
" copy: bool, default=True If False, try to avoid a copy and do inplace scaling instead. This is not guaranteed to always work inplace; e.g. if the data is not a NumPy array or scipy.sparse CSR matrix, a copy may still be returned.\n", " \n", " | \n",
" True | \n", "
| \n", " | \n",
" \n",
" with_mean\n",
" with_mean: bool, default=True If True, center the data before scaling. This does not work (and will raise an exception) when attempted on sparse matrices, because centering them entails building a dense matrix which in common use cases is likely to be too large to fit in memory.\n", " \n", " | \n",
" True | \n", "
| \n", " | \n",
" \n",
" with_std\n",
" with_std: bool, default=True If True, scale the data to unit variance (or equivalently, unit standard deviation).\n", " \n", " | \n",
" True | \n", "
Pipeline(steps=[('standardscaler', StandardScaler()),\n",
" ('svc', SVC(C=0.001, gamma=5))])In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. | \n", " | \n",
" \n",
" copy\n",
" copy: bool, default=True If False, try to avoid a copy and do inplace scaling instead. This is not guaranteed to always work inplace; e.g. if the data is not a NumPy array or scipy.sparse CSR matrix, a copy may still be returned.\n", " \n", " | \n",
" True | \n", "
| \n", " | \n",
" \n",
" with_mean\n",
" with_mean: bool, default=True If True, center the data before scaling. This does not work (and will raise an exception) when attempted on sparse matrices, because centering them entails building a dense matrix which in common use cases is likely to be too large to fit in memory.\n", " \n", " | \n",
" True | \n", "
| \n", " | \n",
" \n",
" with_std\n",
" with_std: bool, default=True If True, scale the data to unit variance (or equivalently, unit standard deviation).\n", " \n", " | \n",
" True | \n", "