sklearn.preprocessing.LabelEncoder — scikit-learn 0.20.4 documentation (original) (raw)
class sklearn.preprocessing. LabelEncoder[source]¶
Encode labels with value between 0 and n_classes-1.
Read more in the User Guide.
| Attributes: | classes_ : array of shape (n_class,) Holds the label for each class. |
|---|
Examples
LabelEncoder can be used to normalize labels.
from sklearn import preprocessing le = preprocessing.LabelEncoder() le.fit([1, 2, 2, 6]) LabelEncoder() le.classes_ array([1, 2, 6]) le.transform([1, 1, 2, 6]) array([0, 0, 1, 2]...) le.inverse_transform([0, 0, 1, 2]) array([1, 1, 2, 6])
It can also be used to transform non-numerical labels (as long as they are hashable and comparable) to numerical labels.
le = preprocessing.LabelEncoder() le.fit(["paris", "paris", "tokyo", "amsterdam"]) LabelEncoder() list(le.classes_) ['amsterdam', 'paris', 'tokyo'] le.transform(["tokyo", "tokyo", "paris"]) array([2, 2, 1]...) list(le.inverse_transform([2, 2, 1])) ['tokyo', 'tokyo', 'paris']
Methods
| fit(y) | Fit label encoder |
|---|---|
| fit_transform(y) | Fit label encoder and return encoded labels |
| get_params([deep]) | Get parameters for this estimator. |
| inverse_transform(y) | Transform labels back to original encoding. |
| set_params(**params) | Set the parameters of this estimator. |
| transform(y) | Transform labels to normalized encoding. |
__init__($self, /, *args, **kwargs)¶
Initialize self. See help(type(self)) for accurate signature.
Fit label encoder
| Parameters: | y : array-like of shape (n_samples,) Target values. |
|---|---|
| Returns: | self : returns an instance of self. |
Fit label encoder and return encoded labels
| Parameters: | y : array-like of shape [n_samples] Target values. |
|---|---|
| Returns: | y : array-like of shape [n_samples] |
get_params(deep=True)[source]¶
Get parameters for this estimator.
| Parameters: | deep : boolean, optional If True, will return the parameters for this estimator and contained subobjects that are estimators. |
|---|---|
| Returns: | params : mapping of string to any Parameter names mapped to their values. |
Transform labels back to original encoding.
| Parameters: | y : numpy array of shape [n_samples] Target values. |
|---|---|
| Returns: | y : numpy array of shape [n_samples] |
Set the parameters of this estimator.
The method works on simple estimators as well as on nested objects (such as pipelines). The latter have parameters of the form<component>__<parameter> so that it’s possible to update each component of a nested object.
| Returns: | self |
|---|
Transform labels to normalized encoding.
| Parameters: | y : array-like of shape [n_samples] Target values. |
|---|---|
| Returns: | y : array-like of shape [n_samples] |