wehub-resource-sync
64 lines
1.8 KiB
Python
64 lines
1.8 KiB
Python
# coding:utf-8
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import numpy as np
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class BaseEstimator:
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y_required = True
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fit_required = True
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def _setup_input(self, X, y=None):
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"""Ensure inputs to an estimator are in the expected format.
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Ensures X and y are stored as numpy ndarrays by converting from an
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array-like object if necessary. Enables estimators to define whether
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they require a set of y target values or not with y_required, e.g.
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kmeans clustering requires no target labels and is fit against only X.
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Parameters
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----------
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X : array-like
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Feature dataset.
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y : array-like
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Target values. By default is required, but if y_required = false
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then may be omitted.
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"""
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if not isinstance(X, np.ndarray):
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X = np.array(X)
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if X.size == 0:
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raise ValueError("Got an empty matrix.")
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if X.ndim == 1:
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self.n_samples, self.n_features = 1, X.shape
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else:
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self.n_samples, self.n_features = X.shape[0], np.prod(X.shape[1:])
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self.X = X
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if self.y_required:
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if y is None:
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raise ValueError("Missed required argument y")
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if not isinstance(y, np.ndarray):
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y = np.array(y)
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if y.size == 0:
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raise ValueError("The targets array must be no-empty.")
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self.y = y
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def fit(self, X, y=None):
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self._setup_input(X, y)
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def predict(self, X=None):
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if not isinstance(X, np.ndarray):
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X = np.array(X)
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if self.X is not None or not self.fit_required:
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return self._predict(X)
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else:
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raise ValueError("You must call `fit` before `predict`")
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def _predict(self, X=None):
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raise NotImplementedError()
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