TreeClassificationTransformer¶
- class proglearn.TreeClassificationTransformer(kwargs={})[source]¶
- A class used to transform data from a category to a specialized representation. - Parameters
- kwargs : dict, default={} - A dictionary to contain parameters of the tree. 
 - Attributes - transformer - (sklearn.tree.DecisionTreeClassifier) an internal sklearn DecisionTreeClassifier 
Methods Summary
| Fits the transformer to data X with labels y. | |
| Fit to data, then transform it. | |
| Get parameters for this estimator. | |
| Set the parameters of this estimator. | |
| Performs inference using the transformer. | 
- TreeClassificationTransformer.fit(X, y)[source]¶
- Fits the transformer to data X with labels y. - Parameters
- X : ndarray - Input data matrix. - y : ndarray - Output (i.e. response data matrix). 
- Returns
- self : TreeClassificationTransformer - The object itself. 
 
- TreeClassificationTransformer.fit_transform(X, y=None, **fit_params)¶
- Fit to data, then transform it. - Fits transformer to X and y with optional parameters fit_params and returns a transformed version of X. - Parameters
- X : array-like of shape (n_samples, n_features) - Input samples. - y : array-like of shape (n_samples,) or (n_samples, n_outputs), default=None - Target values (None for unsupervised transformations). - **fit_params : dict - Additional fit parameters. 
- Returns
- X_new : ndarray array of shape (n_samples, n_features_new) - Transformed array. 
 
- TreeClassificationTransformer.get_params(deep=True)¶
- Get parameters for this estimator. - Parameters
- deep : bool, default=True - If True, will return the parameters for this estimator and contained subobjects that are estimators. 
- Returns
- params : dict - Parameter names mapped to their values. 
 
- TreeClassificationTransformer.set_params(**params)¶
- Set the parameters of this estimator. - The method works on simple estimators as well as on nested objects (such as - Pipeline). The latter have parameters of the form- <component>__<parameter>so that it's possible to update each component of a nested object.- Parameters
- **params : dict - Estimator parameters. 
- Returns
- self : estimator instance - Estimator instance.