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larsmansFabian Pedregosa
larsmans
authored and
Fabian Pedregosa
committed
DOC: fix typos
s/nn/n/ in dictionary and optional
1 parent 4f85e55 commit 00370c8

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6 files changed

+16
-16
lines changed

6 files changed

+16
-16
lines changed

‎sklearn/base.py

Lines changed: 3 additions & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -30,7 +30,7 @@ def clone(estimator, safe=True):
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"""
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estimator_type = type(estimator)
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# XXX: not handling dictionnaries
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# XXX: not handling dictionaries
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if estimator_type in (list, tuple, set, frozenset):
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return estimator_type([clone(e, safe=safe) for e in estimator])
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elif not hasattr(estimator, '_get_params'):
@@ -75,12 +75,12 @@ def clone(estimator, safe=True):
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###############################################################################
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def _pprint(params, offset=0, printer=repr):
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"""Pretty print the dictionnary 'params'
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"""Pretty print the dictionary 'params'
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Parameters
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----------
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params: dict
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The dictionnary to pretty print
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The dictionary to pretty print
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offset: int
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The offset in characters to add at the begin of each line.

‎sklearn/decomposition/tests/test_fastica.py

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -19,7 +19,7 @@ def center_and_norm(x, axis=-1):
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x: ndarray
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Array with an axis of observations (statistical units) measured on
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random variables.
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axis: int, optionnal
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axis: int, optional
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Axis along which the mean and variance are calculated.
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"""
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x = np.rollaxis(x, axis)

‎sklearn/linear_model/bayes.py

Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -68,7 +68,7 @@ class BayesianRidge(LinearModel):
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If True, the regressors X are normalized
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Default is False
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overwrite_X : boolean, optionnal
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overwrite_X : boolean, optional
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If True, X will not be copied
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Default is False
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@@ -285,7 +285,7 @@ class ARDRegression(LinearModel):
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normalize : boolean, optional
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If True, the regressors X are normalized
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overwrite_X : boolean, optionnal
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overwrite_X : boolean, optional
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If True, X will not be copied
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Default is False
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‎sklearn/linear_model/coordinate_descent.py

Lines changed: 4 additions & 4 deletions
Original file line numberDiff line numberDiff line change
@@ -50,7 +50,7 @@ class ElasticNet(LinearModel):
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max_iter: int, optional
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The maximum number of iterations
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53-
overwrite_X : boolean, optionnal
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overwrite_X : boolean, optional
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If True, X will not be copied
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Default is False
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@@ -199,7 +199,7 @@ class Lasso(ElasticNet):
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normalize : boolean, optional
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If True, the regressors X are normalized
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overwrite_X : boolean, optionnal
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overwrite_X : boolean, optional
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If True, X will not be copied
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Default is False
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@@ -305,7 +305,7 @@ def lasso_path(X, y, eps=1e-3, n_alphas=100, alphas=None,
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normalize : boolean, optional
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If True, the regressors X are normalized
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308-
overwrite_X : boolean, optionnal
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overwrite_X : boolean, optional
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If True, X will not be copied
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Default is False
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@@ -377,7 +377,7 @@ def enet_path(X, y, rho=0.5, eps=1e-3, n_alphas=100, alphas=None,
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normalize : boolean, optional
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If True, the regressors X are normalized
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overwrite_X : boolean, optionnal
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overwrite_X : boolean, optional
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If True, X will not be copied
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Default is False
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‎sklearn/linear_model/least_angle.py

Lines changed: 5 additions & 5 deletions
Original file line numberDiff line numberDiff line change
@@ -324,7 +324,7 @@ class Lars(LinearModel):
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calculations. If set to 'auto' let us decide. The Gram
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matrix can also be passed as argument.
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overwrite_X : boolean, optionnal
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overwrite_X : boolean, optional
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If True, X will not be copied
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Default is False
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@@ -452,7 +452,7 @@ class LassoLars(Lars):
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normalize : boolean, optional
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If True, the regressors X are normalized
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overwrite_X : boolean, optionnal
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overwrite_X : boolean, optional
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If True, X will not be copied
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Default is False
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@@ -632,7 +632,7 @@ class LarsCV(LARS):
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normalize : boolean, optional
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If True, the regressors X are normalized
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635-
overwrite_X : boolean, optionnal
635+
overwrite_X : boolean, optional
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If True, X will not be copied
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Default is False
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@@ -790,7 +790,7 @@ class LassoLarsCV(LarsCV):
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Cholesky diagonal factors. Increase this for very ill-conditioned
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systems.
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overwrite_X : boolean, optionnal
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overwrite_X : boolean, optional
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If True, X will not be copied
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Default is False
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@@ -862,7 +862,7 @@ class LassoLarsIC(LassoLars):
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normalize : boolean, optional
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If True, the regressors X are normalized
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865-
overwrite_X : boolean, optionnal
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overwrite_X : boolean, optional
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Default is False.
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If True, X will be overwritten
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‎sklearn/linear_model/ridge.py

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -140,7 +140,7 @@ class Ridge(LinearModel):
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normalize : boolean, optional
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If True, the regressors X are normalized
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overwrite_X : boolean, optionnal
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overwrite_X : boolean, optional
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If True, X will not be copied
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Default is False
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