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refactor Multidiscretizer to use one per column

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This commit is contained in:
Ricardo Montañana Gómez
2023-02-04 19:23:15 +01:00
parent cf09d92ccc
commit f20496203e
1 changed files with 21 additions and 8 deletions
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29
src/fimdlp/mdlp.py
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@@ -183,25 +183,38 @@ class MultiDiscretizer:
self.algorithm = algorithm self.algorithm = algorithm
self.n_jobs = n_jobs self.n_jobs = n_jobs
def fit_transform(self, X, y, **kwargs): def initial_fit_transform(self, X, y):
X, y = check_X_y(X, y) X, y = check_X_y(X, y)
self.X_ = X self.X_ = X
self.y_ = y self.y_ = y
self.n_features_in_ = X.shape[1] self.n_features_in_ = X.shape[1]
self.discretizer_ = FImdlp(
algorithm=self.algorithm, n_jobs=self.n_jobs
)
self.discretizers_ = [None] * self.n_features_in_ self.discretizers_ = [None] * self.n_features_in_
self.discretized_ = [None] * self.n_features_in_ self.discretized_ = [None] * self.n_features_in_
self.yy_ = [None] * self.n_features_in_ # self.yy_ = [None] * self.n_features_in_
self.X_d_ = self.discretizer_.fit_transform(X, y, **kwargs) self.X_d_ = np.zeros_like(X, dtype=np.int32) - 1
for feature in range(self.n_features_in_):
self.discretizers_[feature] = FImdlp(
algorithm=self.algorithm, n_jobs=self.n_jobs
)
self.discretized_[feature] = self.discretizers_[
feature
].fit_transform(X[:, feature].reshape(-1, 1), y)
# self.yy_[feature] = self.discretizers_[feature].factorize(y)
self.X_d_[:, feature] = self.discretized_[feature].ravel()
return self.X_d_ return self.X_d_
def transform(self, X): def transform(self, X):
X = check_array(X) X = check_array(X)
if not hasattr(self, "discretizer_"): if not hasattr(self, "discretizers_"):
raise ValueError("Must call fit_transform first") raise ValueError("Must call fit_transform first")
return self.discretizer_.transform(X) result = np.zeros_like(X, dtype=np.int32) - 1
for feature in range(self.n_features_in_):
result[:, feature] = (
self.discretizers_[feature]
.transform(X[:, feature].reshape(-1, 1))
.ravel()
)
return result
def join_transform(self, features, target): def join_transform(self, features, target):
"""Join the selected features with the labels and discretize the values """Join the selected features with the labels and discretize the values