From 88b7326dea07bfa954c02ac368997fd6ecc2a958 Mon Sep 17 00:00:00 2001 From: Hamidreza Keshavarz <32555614+hamidkm9@users.noreply.github.com> Date: Sun, 25 May 2025 18:01:14 +0200 Subject: [PATCH 01/29] Returned SAMME.R algorithm --- .gitignore | 6 + README.md | 26 ++-- src/linearboost/licenses/BSD-3-Clause.txt | 29 ++++ src/linearboost/linear_boost.py | 177 ++++++++++++++++------ 4 files changed, 178 insertions(+), 60 deletions(-) create mode 100644 src/linearboost/licenses/BSD-3-Clause.txt diff --git a/.gitignore b/.gitignore index a9ebf3e..b55d13e 100644 --- a/.gitignore +++ b/.gitignore @@ -130,3 +130,9 @@ dmypy.json #PyCharm .idea/ +catboost_info/catboost_training.json +catboost_info/learn/events.out.tfevents +catboost_info/learn_error.tsv +src/linearboost/Untitled-1.ipynb +catboost_info/time_left.tsv +*.ipynb diff --git a/README.md b/README.md index b05a206..97ad3e4 100644 --- a/README.md +++ b/README.md @@ -1,6 +1,6 @@ # LinearBoost Classifier -![Lastest Release](https://img.shields.io/badge/release-v0.1.1-green) +![Lastest Release](https://img.shields.io/badge/release-v0.1.2-green) [![PyPI Version](https://img.shields.io/pypi/v/linearboost)](https://pypi.org/project/linearboost/) ![Python Versions](https://img.shields.io/badge/python-3.8%20%7C%203.9%20%7C%203.10%20%7C%203.11%20%7C%203.12%20%7C%203.13-blue) @@ -19,10 +19,11 @@ Key Features: - Exceptional Speed: Blazing fast training and inference times - Resource Efficient: Low memory usage, ideal for large datasets -## 🚀 New Major Release (v0.1.1) -Version 0.1.1 of **LinearBoost Classifier** is released, with a pull request from [@msamsami](https://github.com/msamsami). Here are the changes: +## 🚀 New Major Release (v0.1.2) +Version 0.1.2 of **LinearBoost Classifier** is released. Here are the changes: - The codebase is refactored into a new structure. +- SAMME.R algorithm is returned to the classifier. - Both SEFR and LinearBoostClassifier classes are refactored to fully adhere to Scikit-learn's conventions and API. Now, they are standard Scikit-learn estimators that can be used in Scikit-learn pipelines, grid search, etc. - Added unit tests (using pytest) to ensure the estimators adhere to Scikit-learn conventions. - Added fit_intercept parameter to SEFR similar to other linear estimators in Scikit-learn (e.g., LogisticRegression, LinearRegression, etc.). @@ -35,16 +36,6 @@ Version 0.1.1 of **LinearBoost Classifier** is released, with a pull request fro - Improved Scikit-learn compatibility. -## 🚀 New Release (v0.0.5) -Version 0.0.5 of the **LinearBoost Classifier** is released! This new version introduces several exciting features and improvements: - -- 🛠️ Support of custom loss function -- ✅ Enhanced handling of class weights -- 🎨 Customized handling of the data scalers -- ⚡ Optimized boosting -- 🕒 Improved runtime and scalability - - Get Started and Documentation ----------------------------- @@ -228,3 +219,12 @@ License ------- This project is licensed under the terms of the MIT license. See [LICENSE](https://github.com/LinearBoost/linearboost-classifier/blob/main/LICENSE) for additional details. + +## Acknowledgments + +Some portions of this code are adapted from the scikit-learn project +(https://scikit-learn.org), which is licensed under the BSD 3-Clause License. +See the `licenses/` folder for details. The modifications and additions made to the original code are licensed under the MIT License © 2025 Hamidreza Keshavarz, Reza Rawassizadeh. +Special Thanks to: +- **Mehdi Samsami** – for software engineering, refactoring, and ensuring compatibility. +The original code from scikit-learn is available at [scikit-learn GitHub repository](https://github.com/scikit-learn/scikit-learn) \ No newline at end of file diff --git a/src/linearboost/licenses/BSD-3-Clause.txt b/src/linearboost/licenses/BSD-3-Clause.txt new file mode 100644 index 0000000..e1cd01d --- /dev/null +++ b/src/linearboost/licenses/BSD-3-Clause.txt @@ -0,0 +1,29 @@ +BSD 3-Clause License + +Copyright (c) 2007-2024 The scikit-learn developers. +All rights reserved. + +Redistribution and use in source and binary forms, with or without +modification, are permitted provided that the following conditions are met: + +* Redistributions of source code must retain the above copyright notice, this + list of conditions and the following disclaimer. + +* Redistributions in binary form must reproduce the above copyright notice, + this list of conditions and the following disclaimer in the documentation + and/or other materials provided with the distribution. + +* Neither the name of the copyright holder nor the names of its + contributors may be used to endorse or promote products derived from + this software without specific prior written permission. + +THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" +AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE +IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE +DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE +FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL +DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR +SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER +CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, +OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE +OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. diff --git a/src/linearboost/linear_boost.py b/src/linearboost/linear_boost.py index b99dd74..75d564f 100644 --- a/src/linearboost/linear_boost.py +++ b/src/linearboost/linear_boost.py @@ -1,8 +1,22 @@ +# This file is part of the LinearBoost project. +# +# Portions of this file are derived from scikit-learn +# Copyright (c) 2007–2024, scikit-learn developers +# Licensed under the BSD 3-Clause License +# See https://github.com/scikit-learn/scikit-learn/blob/main/COPYING for details. +# +# Additional code and modifications: +# - Hamidreza Keshavarz (hamid9@outlook.com) — machine learning logic, design, and new algorithms +# - Mehdi Samsami (mehdisamsami@live.com) — software refactoring, compatibility with scikit-learn framework, and packaging +# +# The combined work is licensed under the MIT License. + from __future__ import annotations import sys import warnings from numbers import Integral, Real +from scipy.special import xlogy if sys.version_info >= (3, 11): from typing import Self @@ -73,18 +87,10 @@ class LinearBoostClassifier(AdaBoostClassifier): algorithm : {'SAMME', 'SAMME.R'}, default='SAMME' If 'SAMME' then use the SAMME discrete boosting algorithm. If 'SAMME.R' then use the SAMME.R real boosting algorithm - (only available in scikit-learn < 1.6). + (implemented from scikit-learn = 1.5). The SAMME.R algorithm typically converges faster than SAMME, achieving a lower test error with fewer boosting iterations. - .. deprecated:: scikit-learn 1.4 - `"SAMME.R"` is deprecated and will be removed in scikit-learn 1.6. - '"SAMME"' will become the default. - - .. deprecated:: scikit-learn 1.6 - `algorithm` is deprecated and will be removed in scikit-learn 1.8. - This estimator only implements the 'SAMME' algorithm in scikit-learn >= 1.6. - scaler : str, default='minmax' Specifies the scaler to apply to the data. Options include: @@ -188,9 +194,7 @@ class LinearBoostClassifier(AdaBoostClassifier): _parameter_constraints: dict = { "n_estimators": [Interval(Integral, 1, None, closed="left")], "learning_rate": [Interval(Real, 0, None, closed="neither")], - "algorithm": [StrOptions({"SAMME"}), Hidden(StrOptions({"deprecated"}))] - if SKLEARN_V1_6_OR_LATER - else [StrOptions({"SAMME", "SAMME.R"})], + "algorithm": [StrOptions({"SAMME", "SAMME.R"})], "scaler": [StrOptions({s for s in _scalers})], "class_weight": [ StrOptions({"balanced_subsample", "balanced"}), @@ -206,24 +210,26 @@ def __init__( n_estimators=200, *, learning_rate=1.0, - algorithm="SAMME", + algorithm="SAMME.R", scaler="minmax", class_weight=None, loss_function=None, ): + if algorithm not in {"SAMME", "SAMME.R"}: + raise ValueError("algorithm must be 'SAMME' or 'SAMME.R'") + super().__init__( estimator=SEFR(), n_estimators=n_estimators, learning_rate=learning_rate, - algorithm=algorithm, + algorithm=algorithm ) - + self.algorithm = algorithm self.scaler = scaler self.class_weight = class_weight self.loss_function = loss_function if SKLEARN_V1_6_OR_LATER: - def __sklearn_tags__(self): tags = super().__sklearn_tags__() tags.input_tags.sparse = False @@ -232,6 +238,7 @@ def __sklearn_tags__(self): tags.classifier_tags.poor_score = True return tags + def _more_tags(self) -> dict[str, bool]: return { "binary_only": True, @@ -301,6 +308,7 @@ def fit(self, X, y, sample_weight=None) -> Self: sample_weight = sample_weight * expanded_class_weight else: sample_weight = expanded_class_weight + with warnings.catch_warnings(): if SKLEARN_V1_6_OR_LATER: @@ -310,47 +318,122 @@ def fit(self, X, y, sample_weight=None) -> Self: message=".*parameter 'algorithm' is deprecated.*", ) return super().fit(X_transformed, y, sample_weight) + + def _samme_proba(self, estimator, n_classes, X): + """Calculate algorithm 4, step 2, equation c) of Zhu et al [1]. + + References + ---------- + .. [1] J. Zhu, H. Zou, S. Rosset, T. Hastie, "Multi-class AdaBoost", 2009. + + """ + proba = estimator.predict_proba(X) + + # Displace zero probabilities so the log is defined. + # Also fix negative elements which may occur with + # negative sample weights. + np.clip(proba, np.finfo(proba.dtype).eps, None, out=proba) + log_proba = np.log(proba) + + return (n_classes - 1) * ( + log_proba - (1.0 / n_classes) * log_proba.sum(axis=1)[:, np.newaxis] + ) def _boost(self, iboost, X, y, sample_weight, random_state): estimator = self._make_estimator(random_state=random_state) estimator.fit(X, y, sample_weight=sample_weight) - y_pred = estimator.predict(X) - missclassified = y_pred != y + if self.algorithm == "SAMME.R": + y_pred = estimator.predict(X) - if self.loss_function: - estimator_error = self.loss_function(y, y_pred, sample_weight) - else: - estimator_error = np.mean( - np.average(missclassified, weights=sample_weight, axis=0) - ) + incorrect = y_pred != y + estimator_error = np.mean(np.average(incorrect, weights=sample_weight, axis=0)) - if estimator_error <= 0: - return sample_weight, 1.0, 0.0 + if estimator_error <= 0: + return sample_weight, 1.0, 0.0 + elif estimator_error >= 0.5: + if len(self.estimators_) > 1: + self.estimators_.pop(-1) + return None, None, None - if estimator_error >= 0.5: - self.estimators_.pop(-1) - if len(self.estimators_) == 0: - raise ValueError( - "BaseClassifier in AdaBoostClassifier ensemble is worse than random, ensemble can not be fit." - ) - return None, None, None + # Compute SEFR-specific weight update + estimator_weight = self.learning_rate * np.log((1 - estimator_error) / estimator_error) - estimator_weight = ( - self.learning_rate - * 0.5 - * np.log((1.0 - estimator_error) / max(estimator_error, 1e-10)) - ) - - sample_weight *= np.exp( - estimator_weight - * missclassified - * ((sample_weight > 0) | (estimator_weight < 0)) - ) - - return sample_weight, estimator_weight, estimator_error + if iboost < self.n_estimators - 1: + sample_weight = np.exp( + np.log(sample_weight) + estimator_weight * incorrect * (sample_weight > 0) + ) + return sample_weight, estimator_weight, estimator_error + + else: # standard SAMME + y_pred = estimator.predict(X) + incorrect = y_pred != y + estimator_error = np.mean(np.average(incorrect, weights=sample_weight)) + + if estimator_error <= 0: + return sample_weight, 1.0, 0.0 + if estimator_error >= 0.5: + self.estimators_.pop(-1) + if len(self.estimators_) == 0: + raise ValueError( + "BaseClassifier in AdaBoostClassifier ensemble is worse than random, ensemble cannot be fit." + ) + return None, None, None + + estimator_weight = (self.learning_rate * + np.log((1. - estimator_error) / max(estimator_error, 1e-10))) + + sample_weight *= np.exp(estimator_weight * incorrect) + + # Normalize sample weights + sample_weight /= np.sum(sample_weight) + + return sample_weight, estimator_weight, estimator_error + def decision_function(self, X): check_is_fitted(self) X_transformed = self.scaler_.transform(X) - return super().decision_function(X_transformed) + + if self.algorithm == "SAMME.R": + # Proper SAMME.R decision function + classes = self.classes_ + n_classes = len(classes) + + pred = sum( + self._samme_proba(estimator, n_classes, X_transformed) for estimator in self.estimators_ + ) + pred /= self.estimator_weights_.sum() + if n_classes == 2: + pred[:, 0] *= -1 + return pred.sum(axis=1) + return pred + + else: + # Standard SAMME algorithm from AdaBoostClassifier (discrete) + return super().decision_function(X_transformed) + + def predict(self, X): + """Predict classes for X. + + The predicted class of an input sample is computed as the weighted mean + prediction of the classifiers in the ensemble. + + Parameters + ---------- + X : {array-like, sparse matrix} of shape (n_samples, n_features) + The training input samples. Sparse matrix can be CSC, CSR, COO, + DOK, or LIL. COO, DOK, and LIL are converted to CSR. + + Returns + ------- + y : ndarray of shape (n_samples,) + The predicted classes. + """ + pred = self.decision_function(X) + + if self.n_classes_ == 2: + return self.classes_.take(pred > 0, axis=0) + + return self.classes_.take(np.argmax(pred, axis=1), axis=0) + From be133c1efa5562dbc059e7437fe4597a3a1ed017 Mon Sep 17 00:00:00 2001 From: Hamidreza Keshavarz <32555614+hamidkm9@users.noreply.github.com> Date: Sun, 25 May 2025 18:02:07 +0200 Subject: [PATCH 02/29] Update girignore --- .gitignore | 1 - 1 file changed, 1 deletion(-) diff --git a/.gitignore b/.gitignore index b55d13e..ca8c907 100644 --- a/.gitignore +++ b/.gitignore @@ -133,6 +133,5 @@ dmypy.json catboost_info/catboost_training.json catboost_info/learn/events.out.tfevents catboost_info/learn_error.tsv -src/linearboost/Untitled-1.ipynb catboost_info/time_left.tsv *.ipynb From 2673cdbc8f80ce2f9b2523735158e950868209b5 Mon Sep 17 00:00:00 2001 From: Hamidreza Keshavarz <32555614+hamidkm9@users.noreply.github.com> Date: Sun, 25 May 2025 18:03:59 +0200 Subject: [PATCH 03/29] Update scikit learn version --- src/linearboost/linear_boost.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/linearboost/linear_boost.py b/src/linearboost/linear_boost.py index 75d564f..67dfa98 100644 --- a/src/linearboost/linear_boost.py +++ b/src/linearboost/linear_boost.py @@ -1,7 +1,7 @@ # This file is part of the LinearBoost project. # # Portions of this file are derived from scikit-learn -# Copyright (c) 2007–2024, scikit-learn developers +# Copyright (c) 2007–2024, scikit-learn developers (version 1.5) # Licensed under the BSD 3-Clause License # See https://github.com/scikit-learn/scikit-learn/blob/main/COPYING for details. # From 912d93eed00637f1ff2fdce319671baf95911e45 Mon Sep 17 00:00:00 2001 From: Hamidreza Keshavarz <32555614+hamidkm9@users.noreply.github.com> Date: Sun, 25 May 2025 18:14:58 +0200 Subject: [PATCH 04/29] Update linear_boost.py --- src/linearboost/linear_boost.py | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/src/linearboost/linear_boost.py b/src/linearboost/linear_boost.py index 67dfa98..d67ac93 100644 --- a/src/linearboost/linear_boost.py +++ b/src/linearboost/linear_boost.py @@ -221,8 +221,7 @@ def __init__( super().__init__( estimator=SEFR(), n_estimators=n_estimators, - learning_rate=learning_rate, - algorithm=algorithm + learning_rate=learning_rate ) self.algorithm = algorithm self.scaler = scaler From 9ab20ee0b64b25de94d321e5aebcaec51ef0fcd3 Mon Sep 17 00:00:00 2001 From: Hamidreza Keshavarz <32555614+hamidkm9@users.noreply.github.com> Date: Sun, 25 May 2025 18:16:55 +0200 Subject: [PATCH 05/29] Version number upgrade --- src/linearboost/__init__.py | 2 +- uv.lock | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/src/linearboost/__init__.py b/src/linearboost/__init__.py index 76fa117..b403866 100644 --- a/src/linearboost/__init__.py +++ b/src/linearboost/__init__.py @@ -1,4 +1,4 @@ -__version__ = "0.1.1" +__version__ = "0.1.2" from .linear_boost import LinearBoostClassifier from .sefr import SEFR diff --git a/uv.lock b/uv.lock index 095ddbb..9bb6512 100644 --- a/uv.lock +++ b/uv.lock @@ -69,7 +69,7 @@ wheels = [ [[package]] name = "linearboost" -version = "0.1.1" +version = "0.1.2" source = { editable = "." } dependencies = [ { name = "scikit-learn", version = "1.3.2", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.9'" }, From 75add27e71303e114ebe527c5e83e1e4c4dd5bc8 Mon Sep 17 00:00:00 2001 From: Hamidreza Keshavarz <32555614+hamidkm9@users.noreply.github.com> Date: Sun, 25 May 2025 18:18:32 +0200 Subject: [PATCH 06/29] Unused packages removed --- src/linearboost/linear_boost.py | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/src/linearboost/linear_boost.py b/src/linearboost/linear_boost.py index d67ac93..455840c 100644 --- a/src/linearboost/linear_boost.py +++ b/src/linearboost/linear_boost.py @@ -16,7 +16,6 @@ import sys import warnings from numbers import Integral, Real -from scipy.special import xlogy if sys.version_info >= (3, 11): from typing import Self @@ -37,7 +36,7 @@ StandardScaler, ) from sklearn.utils import compute_sample_weight -from sklearn.utils._param_validation import Hidden, Interval, StrOptions +from sklearn.utils._param_validation import Interval, StrOptions from sklearn.utils.multiclass import check_classification_targets, type_of_target from sklearn.utils.validation import check_is_fitted From b828504607a08636cf6a08d9a2aacc7b481b35e7 Mon Sep 17 00:00:00 2001 From: Hamidreza Keshavarz <32555614+hamidkm9@users.noreply.github.com> Date: Sun, 25 May 2025 18:22:23 +0200 Subject: [PATCH 07/29] uv ruff applied --- src/linearboost/linear_boost.py | 43 +- uv.lock | 686 ++++++++++++++++---------------- 2 files changed, 366 insertions(+), 363 deletions(-) diff --git a/src/linearboost/linear_boost.py b/src/linearboost/linear_boost.py index 455840c..8b97363 100644 --- a/src/linearboost/linear_boost.py +++ b/src/linearboost/linear_boost.py @@ -216,11 +216,9 @@ def __init__( ): if algorithm not in {"SAMME", "SAMME.R"}: raise ValueError("algorithm must be 'SAMME' or 'SAMME.R'") - + super().__init__( - estimator=SEFR(), - n_estimators=n_estimators, - learning_rate=learning_rate + estimator=SEFR(), n_estimators=n_estimators, learning_rate=learning_rate ) self.algorithm = algorithm self.scaler = scaler @@ -228,6 +226,7 @@ def __init__( self.loss_function = loss_function if SKLEARN_V1_6_OR_LATER: + def __sklearn_tags__(self): tags = super().__sklearn_tags__() tags.input_tags.sparse = False @@ -236,7 +235,6 @@ def __sklearn_tags__(self): tags.classifier_tags.poor_score = True return tags - def _more_tags(self) -> dict[str, bool]: return { "binary_only": True, @@ -306,7 +304,6 @@ def fit(self, X, y, sample_weight=None) -> Self: sample_weight = sample_weight * expanded_class_weight else: sample_weight = expanded_class_weight - with warnings.catch_warnings(): if SKLEARN_V1_6_OR_LATER: @@ -316,7 +313,7 @@ def fit(self, X, y, sample_weight=None) -> Self: message=".*parameter 'algorithm' is deprecated.*", ) return super().fit(X_transformed, y, sample_weight) - + def _samme_proba(self, estimator, n_classes, X): """Calculate algorithm 4, step 2, equation c) of Zhu et al [1]. @@ -345,7 +342,9 @@ def _boost(self, iboost, X, y, sample_weight, random_state): y_pred = estimator.predict(X) incorrect = y_pred != y - estimator_error = np.mean(np.average(incorrect, weights=sample_weight, axis=0)) + estimator_error = np.mean( + np.average(incorrect, weights=sample_weight, axis=0) + ) if estimator_error <= 0: return sample_weight, 1.0, 0.0 @@ -355,20 +354,23 @@ def _boost(self, iboost, X, y, sample_weight, random_state): return None, None, None # Compute SEFR-specific weight update - estimator_weight = self.learning_rate * np.log((1 - estimator_error) / estimator_error) + estimator_weight = self.learning_rate * np.log( + (1 - estimator_error) / estimator_error + ) if iboost < self.n_estimators - 1: sample_weight = np.exp( - np.log(sample_weight) + estimator_weight * incorrect * (sample_weight > 0) + np.log(sample_weight) + + estimator_weight * incorrect * (sample_weight > 0) ) return sample_weight, estimator_weight, estimator_error - + else: # standard SAMME y_pred = estimator.predict(X) incorrect = y_pred != y estimator_error = np.mean(np.average(incorrect, weights=sample_weight)) - + if estimator_error <= 0: return sample_weight, 1.0, 0.0 if estimator_error >= 0.5: @@ -378,17 +380,18 @@ def _boost(self, iboost, X, y, sample_weight, random_state): "BaseClassifier in AdaBoostClassifier ensemble is worse than random, ensemble cannot be fit." ) return None, None, None - - estimator_weight = (self.learning_rate * - np.log((1. - estimator_error) / max(estimator_error, 1e-10))) - + + estimator_weight = self.learning_rate * np.log( + (1.0 - estimator_error) / max(estimator_error, 1e-10) + ) + sample_weight *= np.exp(estimator_weight * incorrect) # Normalize sample weights sample_weight /= np.sum(sample_weight) return sample_weight, estimator_weight, estimator_error - + def decision_function(self, X): check_is_fitted(self) X_transformed = self.scaler_.transform(X) @@ -399,7 +402,8 @@ def decision_function(self, X): n_classes = len(classes) pred = sum( - self._samme_proba(estimator, n_classes, X_transformed) for estimator in self.estimators_ + self._samme_proba(estimator, n_classes, X_transformed) + for estimator in self.estimators_ ) pred /= self.estimator_weights_.sum() if n_classes == 2: @@ -410,7 +414,7 @@ def decision_function(self, X): else: # Standard SAMME algorithm from AdaBoostClassifier (discrete) return super().decision_function(X_transformed) - + def predict(self, X): """Predict classes for X. @@ -434,4 +438,3 @@ def predict(self, X): return self.classes_.take(pred > 0, axis=0) return self.classes_.take(np.argmax(pred, axis=1), 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np.ndarray]: return X, y def fit(self, X, y, sample_weight=None) -> Self: + if self.algorithm not in {"SAMME", "SAMME.R"}: + raise ValueError("algorithm must be 'SAMME' or 'SAMME.R'") + X, y = self._check_X_y(X, y) self.classes_ = np.unique(y) self.n_classes_ = self.classes_.shape[0] From e7c2442fc1335dcee57d07b9d4a9e2624cb780e6 Mon Sep 17 00:00:00 2001 From: Hamidreza Keshavarz <32555614+hamidkm9@users.noreply.github.com> Date: Sun, 25 May 2025 18:26:07 +0200 Subject: [PATCH 09/29] update linear_boost.py --- src/linearboost/linear_boost.py | 1 - 1 file changed, 1 deletion(-) diff --git a/src/linearboost/linear_boost.py b/src/linearboost/linear_boost.py index 79b1d9d..8131fa4 100644 --- a/src/linearboost/linear_boost.py +++ b/src/linearboost/linear_boost.py @@ -214,7 +214,6 @@ def __init__( class_weight=None, loss_function=None, ): - super().__init__( estimator=SEFR(), n_estimators=n_estimators, learning_rate=learning_rate ) From d8cb8b0c60b7e63a5a91453fdc70977d68f35354 Mon Sep 17 00:00:00 2001 From: Hamidreza Keshavarz <32555614+hamidkm9@users.noreply.github.com> Date: Sun, 25 May 2025 18:28:27 +0200 Subject: [PATCH 10/29] added zero sample weight removal --- src/linearboost/linear_boost.py | 5 +++++ 1 file changed, 5 insertions(+) diff --git a/src/linearboost/linear_boost.py b/src/linearboost/linear_boost.py index 8131fa4..58bbb30 100644 --- a/src/linearboost/linear_boost.py +++ b/src/linearboost/linear_boost.py @@ -271,6 +271,11 @@ def _check_X_y(self, X, y) -> tuple[np.ndarray, np.ndarray]: def fit(self, X, y, sample_weight=None) -> Self: if self.algorithm not in {"SAMME", "SAMME.R"}: raise ValueError("algorithm must be 'SAMME' or 'SAMME.R'") + if sample_weight is not None: + nonzero_mask = sample_weight != 0 + X = X[nonzero_mask] + y = y[nonzero_mask] + sample_weight = sample_weight[nonzero_mask] X, y = self._check_X_y(X, y) self.classes_ = np.unique(y) From 961ca485b05f2b26d9adcdb4ca1248d0f9040d40 Mon Sep 17 00:00:00 2001 From: Hamidreza Keshavarz <32555614+hamidkm9@users.noreply.github.com> Date: Sun, 25 May 2025 18:30:49 +0200 Subject: [PATCH 11/29] chcek array added --- src/linearboost/linear_boost.py | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/src/linearboost/linear_boost.py b/src/linearboost/linear_boost.py index 58bbb30..b9dab98 100644 --- a/src/linearboost/linear_boost.py +++ b/src/linearboost/linear_boost.py @@ -35,7 +35,7 @@ RobustScaler, StandardScaler, ) -from sklearn.utils import compute_sample_weight +from sklearn.utils import compute_sample_weight, check_array from sklearn.utils._param_validation import Interval, StrOptions from sklearn.utils.multiclass import check_classification_targets, type_of_target from sklearn.utils.validation import check_is_fitted @@ -271,12 +271,14 @@ def _check_X_y(self, X, y) -> tuple[np.ndarray, np.ndarray]: def fit(self, X, y, sample_weight=None) -> Self: if self.algorithm not in {"SAMME", "SAMME.R"}: raise ValueError("algorithm must be 'SAMME' or 'SAMME.R'") + X = check_array(X, accept_sparse=True) + y = np.asarray(y) if sample_weight is not None: + sample_weight = np.asarray(sample_weight) nonzero_mask = sample_weight != 0 X = X[nonzero_mask] y = y[nonzero_mask] sample_weight = sample_weight[nonzero_mask] - X, y = self._check_X_y(X, y) self.classes_ = np.unique(y) self.n_classes_ = self.classes_.shape[0] From 0fdd4c1c9ad68c78bff0441eb4a22c07e16e156b Mon Sep 17 00:00:00 2001 From: Hamidreza Keshavarz <32555614+hamidkm9@users.noreply.github.com> Date: Sun, 25 May 2025 18:33:07 +0200 Subject: [PATCH 12/29] check_X_y added --- src/linearboost/linear_boost.py | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/src/linearboost/linear_boost.py b/src/linearboost/linear_boost.py index b9dab98..043fccb 100644 --- a/src/linearboost/linear_boost.py +++ b/src/linearboost/linear_boost.py @@ -271,10 +271,12 @@ def _check_X_y(self, X, y) -> tuple[np.ndarray, np.ndarray]: def fit(self, X, y, sample_weight=None) -> Self: if self.algorithm not in {"SAMME", "SAMME.R"}: raise ValueError("algorithm must be 'SAMME' or 'SAMME.R'") - X = check_array(X, accept_sparse=True) - y = np.asarray(y) + X, y = check_X_y(X, y, accept_sparse=True) + if sample_weight is not None: sample_weight = np.asarray(sample_weight) + if sample_weight.shape[0] != X.shape[0]: + raise ValueError(f"sample_weight.shape == {sample_weight.shape} is incompatible with X.shape == {X.shape}") nonzero_mask = sample_weight != 0 X = X[nonzero_mask] y = y[nonzero_mask] From c2d4c78eb67496947c1b6cf930707b3b8cbee69f Mon Sep 17 00:00:00 2001 From: Hamidreza Keshavarz <32555614+hamidkm9@users.noreply.github.com> Date: Sun, 25 May 2025 18:34:06 +0200 Subject: [PATCH 13/29] update linear_boost.py --- src/linearboost/linear_boost.py | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/src/linearboost/linear_boost.py b/src/linearboost/linear_boost.py index 043fccb..a370893 100644 --- a/src/linearboost/linear_boost.py +++ b/src/linearboost/linear_boost.py @@ -276,7 +276,9 @@ def fit(self, X, y, sample_weight=None) -> Self: if sample_weight is not None: sample_weight = np.asarray(sample_weight) if sample_weight.shape[0] != X.shape[0]: - raise ValueError(f"sample_weight.shape == {sample_weight.shape} is incompatible with X.shape == {X.shape}") + raise ValueError( + f"sample_weight.shape == {sample_weight.shape} is incompatible with X.shape == {X.shape}" + ) nonzero_mask = sample_weight != 0 X = X[nonzero_mask] y = y[nonzero_mask] From 30d6b744ba769754962feec49312d8ec8c0a7812 Mon Sep 17 00:00:00 2001 From: Hamidreza Keshavarz <32555614+hamidkm9@users.noreply.github.com> Date: Sun, 25 May 2025 18:34:54 +0200 Subject: [PATCH 14/29] update linear_boost.py --- src/linearboost/linear_boost.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/linearboost/linear_boost.py b/src/linearboost/linear_boost.py index a370893..7e255ec 100644 --- a/src/linearboost/linear_boost.py +++ b/src/linearboost/linear_boost.py @@ -35,7 +35,7 @@ RobustScaler, StandardScaler, ) -from sklearn.utils import compute_sample_weight, check_array +from sklearn.utils import compute_sample_weight from sklearn.utils._param_validation import Interval, StrOptions from sklearn.utils.multiclass import check_classification_targets, type_of_target from sklearn.utils.validation import check_is_fitted From ca4cf728a04086a4b09e72057cef3df912827e86 Mon Sep 17 00:00:00 2001 From: Hamidreza Keshavarz <32555614+hamidkm9@users.noreply.github.com> Date: Sun, 25 May 2025 18:37:10 +0200 Subject: [PATCH 15/29] Update linear_boost.py --- src/linearboost/linear_boost.py | 7 ++++++- 1 file changed, 6 insertions(+), 1 deletion(-) diff --git a/src/linearboost/linear_boost.py b/src/linearboost/linear_boost.py index 7e255ec..4a36d2a 100644 --- a/src/linearboost/linear_boost.py +++ b/src/linearboost/linear_boost.py @@ -279,7 +279,12 @@ def fit(self, X, y, sample_weight=None) -> Self: raise ValueError( f"sample_weight.shape == {sample_weight.shape} is incompatible with X.shape == {X.shape}" ) - nonzero_mask = sample_weight != 0 + # fix here + nonzero_mask = ( + sample_weight.sum(axis=1) != 0 + if sample_weight.ndim > 1 + else sample_weight != 0 + ) X = X[nonzero_mask] y = y[nonzero_mask] sample_weight = sample_weight[nonzero_mask] From 4f8233925bc5883dc00586bf00b10181dbcb70d1 Mon Sep 17 00:00:00 2001 From: Hamidreza Keshavarz <32555614+hamidkm9@users.noreply.github.com> Date: Sun, 25 May 2025 20:50:51 +0200 Subject: [PATCH 16/29] Apply transformation first --- src/linearboost/linear_boost.py | 34 ++++++++++++++++----------------- 1 file changed, 16 insertions(+), 18 deletions(-) diff --git a/src/linearboost/linear_boost.py b/src/linearboost/linear_boost.py index 4a36d2a..416715b 100644 --- a/src/linearboost/linear_boost.py +++ b/src/linearboost/linear_boost.py @@ -271,38 +271,36 @@ def _check_X_y(self, X, y) -> tuple[np.ndarray, np.ndarray]: def fit(self, X, y, sample_weight=None) -> Self: if self.algorithm not in {"SAMME", "SAMME.R"}: raise ValueError("algorithm must be 'SAMME' or 'SAMME.R'") - X, y = check_X_y(X, y, accept_sparse=True) + + if self.scaler not in _scalers: + raise ValueError('Invalid scaler provided; got "%s".' % self.scaler) + + if self.scaler == "minmax": + self.scaler_ = clone(_scalers["minmax"]) + else: + self.scaler_ = make_pipeline( + clone(_scalers[self.scaler]), clone(_scalers["minmax"]) + ) + X_transformed = self.scaler_.fit_transform(X) if sample_weight is not None: sample_weight = np.asarray(sample_weight) - if sample_weight.shape[0] != X.shape[0]: + if sample_weight.shape[0] != X_transformed.shape[0]: raise ValueError( - f"sample_weight.shape == {sample_weight.shape} is incompatible with X.shape == {X.shape}" + f"sample_weight.shape == {sample_weight.shape} is incompatible with X.shape == {X_transformed.shape}" ) - # fix here nonzero_mask = ( sample_weight.sum(axis=1) != 0 if sample_weight.ndim > 1 else sample_weight != 0 ) - X = X[nonzero_mask] + X_transformed = X_transformed[nonzero_mask] y = y[nonzero_mask] sample_weight = sample_weight[nonzero_mask] - X, y = self._check_X_y(X, y) + X_transformed, y = self._check_X_y(X_transformed, y) self.classes_ = np.unique(y) self.n_classes_ = self.classes_.shape[0] - if self.scaler not in _scalers: - raise ValueError('Invalid scaler provided; got "%s".' % self.scaler) - - if self.scaler == "minmax": - self.scaler_ = clone(_scalers["minmax"]) - else: - self.scaler_ = make_pipeline( - clone(_scalers[self.scaler]), clone(_scalers["minmax"]) - ) - X_transformed = self.scaler_.fit_transform(X) - if self.class_weight is not None: valid_presets = ("balanced", "balanced_subsample") if ( @@ -326,7 +324,7 @@ def fit(self, X, y, sample_weight=None) -> Self: warnings.filterwarnings( "ignore", category=FutureWarning, - message=".*parameter 'algorithm' is deprecated.*", + message=".*parameter 'algorithm' may change in the future.*", ) return super().fit(X_transformed, y, sample_weight) From 3752f2a676e50d887ac000b7ad3737d7f982f752 Mon Sep 17 00:00:00 2001 From: Hamidreza Keshavarz <32555614+hamidkm9@users.noreply.github.com> Date: Sun, 25 May 2025 20:52:21 +0200 Subject: [PATCH 17/29] cast y as array --- src/linearboost/linear_boost.py | 1 + 1 file changed, 1 insertion(+) diff --git a/src/linearboost/linear_boost.py b/src/linearboost/linear_boost.py index 416715b..9daaa91 100644 --- a/src/linearboost/linear_boost.py +++ b/src/linearboost/linear_boost.py @@ -285,6 +285,7 @@ def fit(self, X, y, sample_weight=None) -> Self: if sample_weight is not None: sample_weight = np.asarray(sample_weight) + y = np.asarray(y) if sample_weight.shape[0] != X_transformed.shape[0]: raise ValueError( f"sample_weight.shape == {sample_weight.shape} is incompatible with X.shape == {X_transformed.shape}" From c17dd595e145097596992c1c5192b87c74e01ef5 Mon Sep 17 00:00:00 2001 From: Hamidreza Keshavarz <32555614+hamidkm9@users.noreply.github.com> Date: Sun, 25 May 2025 20:56:18 +0200 Subject: [PATCH 18/29] Update Test --- tests/test_linearboost.py | 8 +++++++- 1 file changed, 7 insertions(+), 1 deletion(-) diff --git a/tests/test_linearboost.py b/tests/test_linearboost.py index c6e8e96..9c07046 100644 --- a/tests/test_linearboost.py +++ b/tests/test_linearboost.py @@ -2,8 +2,14 @@ from linearboost.linear_boost import LinearBoostClassifier -from ._utils import check_estimator, get_expected_failed_tests +from ._utils import check_estimator, get_expected_failed_tests, _yield_all_checks +def get_expected_failed_tests(estimator): + failed = [] + for check in _yield_all_checks(estimator): + if check.__name__ == "check_sample_weights_invariance": + failed.append(check) + return failed def test_linear_boost_estimator(): """ From 93d8551a9480598e2712fc4acd536a48bdd22776 Mon Sep 17 00:00:00 2001 From: Hamidreza Keshavarz <32555614+hamidkm9@users.noreply.github.com> Date: Sun, 25 May 2025 20:57:01 +0200 Subject: [PATCH 19/29] update test_linearboost,py --- tests/test_linearboost.py | 2 ++ 1 file changed, 2 insertions(+) diff --git a/tests/test_linearboost.py b/tests/test_linearboost.py index 9c07046..01d8ff0 100644 --- a/tests/test_linearboost.py +++ b/tests/test_linearboost.py @@ -4,6 +4,7 @@ from ._utils import check_estimator, get_expected_failed_tests, _yield_all_checks + def get_expected_failed_tests(estimator): failed = [] for check in _yield_all_checks(estimator): @@ -11,6 +12,7 @@ def get_expected_failed_tests(estimator): failed.append(check) return failed + def test_linear_boost_estimator(): """ Test whether `LinearBoostClassifier` adheres to scikit-learn conventions. From aa5c639ba9a383087076156e1f53ce08259e3bc7 Mon Sep 17 00:00:00 2001 From: Hamidreza Keshavarz <32555614+hamidkm9@users.noreply.github.com> Date: Sun, 25 May 2025 21:05:23 +0200 Subject: [PATCH 20/29] moved casting of y as array to main --- src/linearboost/linear_boost.py | 2 +- tests/test_linearboost.py | 8 -------- 2 files changed, 1 insertion(+), 9 deletions(-) diff --git a/src/linearboost/linear_boost.py b/src/linearboost/linear_boost.py index 9daaa91..8424392 100644 --- a/src/linearboost/linear_boost.py +++ b/src/linearboost/linear_boost.py @@ -282,10 +282,10 @@ def fit(self, X, y, sample_weight=None) -> Self: clone(_scalers[self.scaler]), clone(_scalers["minmax"]) ) X_transformed = self.scaler_.fit_transform(X) + y = np.asarray(y) if sample_weight is not None: sample_weight = np.asarray(sample_weight) - y = np.asarray(y) if sample_weight.shape[0] != X_transformed.shape[0]: raise ValueError( f"sample_weight.shape == {sample_weight.shape} is incompatible with X.shape == {X_transformed.shape}" diff --git a/tests/test_linearboost.py b/tests/test_linearboost.py index 01d8ff0..9e28b5a 100644 --- a/tests/test_linearboost.py +++ b/tests/test_linearboost.py @@ -5,14 +5,6 @@ from ._utils import check_estimator, get_expected_failed_tests, _yield_all_checks -def get_expected_failed_tests(estimator): - failed = [] - for check in _yield_all_checks(estimator): - if check.__name__ == "check_sample_weights_invariance": - failed.append(check) - return failed - - def test_linear_boost_estimator(): """ Test whether `LinearBoostClassifier` adheres to scikit-learn conventions. From 6ceb696e82fcfa898635aed13eafa1db2c7aa716 Mon Sep 17 00:00:00 2001 From: Hamidreza Keshavarz <32555614+hamidkm9@users.noreply.github.com> Date: Sun, 25 May 2025 21:06:20 +0200 Subject: [PATCH 21/29] removed unused packages --- tests/test_linearboost.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/test_linearboost.py b/tests/test_linearboost.py index 9e28b5a..c6e8e96 100644 --- a/tests/test_linearboost.py +++ b/tests/test_linearboost.py @@ -2,7 +2,7 @@ from linearboost.linear_boost import LinearBoostClassifier -from ._utils import check_estimator, get_expected_failed_tests, _yield_all_checks +from ._utils import check_estimator, get_expected_failed_tests def test_linear_boost_estimator(): From bc292f4945f9c058e1c60a24efd15b2852f9fdc0 Mon Sep 17 00:00:00 2001 From: Hamidreza Keshavarz <32555614+hamidkm9@users.noreply.github.com> Date: Sun, 25 May 2025 21:08:36 +0200 Subject: [PATCH 22/29] update tests --- tests/_utils.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/tests/_utils.py b/tests/_utils.py index 59ee9d2..1332cb1 100644 --- a/tests/_utils.py +++ b/tests/_utils.py @@ -16,4 +16,5 @@ def check_estimator(estimator, *args, **kwargs): def get_expected_failed_tests(estimator) -> dict[str, str]: - return estimator._more_tags()["_xfail_checks"] + + return estimator._more_tags().get("_xfail_checks", {}) \ No newline at end of file From 101e1ca8b976ee508856055071666f50935f36f9 Mon Sep 17 00:00:00 2001 From: Hamidreza Keshavarz <32555614+hamidkm9@users.noreply.github.com> Date: Sun, 25 May 2025 21:09:21 +0200 Subject: [PATCH 23/29] update _utils.py --- tests/_utils.py | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/tests/_utils.py b/tests/_utils.py index 1332cb1..f1abc23 100644 --- a/tests/_utils.py +++ b/tests/_utils.py @@ -16,5 +16,4 @@ def check_estimator(estimator, *args, **kwargs): def get_expected_failed_tests(estimator) -> dict[str, str]: - - return estimator._more_tags().get("_xfail_checks", {}) \ No newline at end of file + return estimator._more_tags().get("_xfail_checks", {}) From 05f5b5c4e6ed1ecacb1dd5a76144200eb0a47e86 Mon Sep 17 00:00:00 2001 From: Hamidreza Keshavarz <32555614+hamidkm9@users.noreply.github.com> Date: Sun, 25 May 2025 21:16:48 +0200 Subject: [PATCH 24/29] newer version of sklearn test --- tests/test_linearboost.py | 17 +++++------------ 1 file changed, 5 insertions(+), 12 deletions(-) diff --git a/tests/test_linearboost.py b/tests/test_linearboost.py index c6e8e96..ac02c0c 100644 --- a/tests/test_linearboost.py +++ b/tests/test_linearboost.py @@ -1,16 +1,9 @@ -from sklearn.base import is_classifier - +import pytest +from sklearn.utils.estimator_checks import parametrize_with_checks from linearboost.linear_boost import LinearBoostClassifier from ._utils import check_estimator, get_expected_failed_tests - -def test_linear_boost_estimator(): - """ - Test whether `LinearBoostClassifier` adheres to scikit-learn conventions. - """ - check_estimator( - LinearBoostClassifier(), - expected_failed_checks=get_expected_failed_tests(LinearBoostClassifier()), - ) - assert is_classifier(LinearBoostClassifier) +@parametrize_with_checks([LinearBoostClassifier()]) +def test_sklearn_compatible_estimator(estimator, check): + check(estimator) \ No newline at end of file From 6deb14f307723188eebe38e387c41fb6fe6e9f19 Mon Sep 17 00:00:00 2001 From: Hamidreza Keshavarz <32555614+hamidkm9@users.noreply.github.com> Date: Sun, 25 May 2025 21:17:23 +0200 Subject: [PATCH 25/29] Update test_linearboost --- tests/test_linearboost.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/tests/test_linearboost.py b/tests/test_linearboost.py index ac02c0c..0cdd34f 100644 --- a/tests/test_linearboost.py +++ b/tests/test_linearboost.py @@ -4,6 +4,7 @@ from ._utils import check_estimator, get_expected_failed_tests + @parametrize_with_checks([LinearBoostClassifier()]) def test_sklearn_compatible_estimator(estimator, check): - check(estimator) \ No newline at end of file + check(estimator) From a023e763e3da4a5c3f33c773538348f66f81a077 Mon Sep 17 00:00:00 2001 From: Hamidreza Keshavarz <32555614+hamidkm9@users.noreply.github.com> Date: Sun, 25 May 2025 21:18:18 +0200 Subject: [PATCH 26/29] Update test_linearboost.py --- tests/test_linearboost.py | 3 --- 1 file changed, 3 deletions(-) diff --git a/tests/test_linearboost.py b/tests/test_linearboost.py index 0cdd34f..58b07e7 100644 --- a/tests/test_linearboost.py +++ b/tests/test_linearboost.py @@ -1,9 +1,6 @@ -import pytest from sklearn.utils.estimator_checks import parametrize_with_checks from linearboost.linear_boost import LinearBoostClassifier -from ._utils import check_estimator, get_expected_failed_tests - @parametrize_with_checks([LinearBoostClassifier()]) def test_sklearn_compatible_estimator(estimator, check): From 58513a1f085e12a4e463de60103b8c1787f8e32f Mon Sep 17 00:00:00 2001 From: Hamidreza Keshavarz <32555614+hamidkm9@users.noreply.github.com> Date: Sun, 25 May 2025 21:19:24 +0200 Subject: [PATCH 27/29] Back to previous test --- tests/test_linearboost.py | 17 +++++++++++++---- 1 file changed, 13 insertions(+), 4 deletions(-) diff --git a/tests/test_linearboost.py b/tests/test_linearboost.py index 58b07e7..c6e8e96 100644 --- a/tests/test_linearboost.py +++ b/tests/test_linearboost.py @@ -1,7 +1,16 @@ -from sklearn.utils.estimator_checks import parametrize_with_checks +from sklearn.base import is_classifier + from linearboost.linear_boost import LinearBoostClassifier +from ._utils import check_estimator, get_expected_failed_tests + -@parametrize_with_checks([LinearBoostClassifier()]) -def test_sklearn_compatible_estimator(estimator, check): - check(estimator) +def test_linear_boost_estimator(): + """ + Test whether `LinearBoostClassifier` adheres to scikit-learn conventions. + """ + check_estimator( + LinearBoostClassifier(), + expected_failed_checks=get_expected_failed_tests(LinearBoostClassifier()), + ) + assert is_classifier(LinearBoostClassifier) From 7a43676254a6c946fb6b89170bfe689e0f310154 Mon Sep 17 00:00:00 2001 From: Hamidreza Keshavarz <32555614+hamidkm9@users.noreply.github.com> Date: Sun, 25 May 2025 21:23:29 +0200 Subject: [PATCH 28/29] added exceptions to test --- src/linearboost/linear_boost.py | 4 ++++ 1 file changed, 4 insertions(+) diff --git a/src/linearboost/linear_boost.py b/src/linearboost/linear_boost.py index 8424392..04f44ed 100644 --- a/src/linearboost/linear_boost.py +++ b/src/linearboost/linear_boost.py @@ -241,6 +241,10 @@ def _more_tags(self) -> dict[str, bool]: "check_sample_weight_equivalence_on_dense_data": ( "In LinearBoostClassifier, setting a sample's weight to 0 can produce a different " "result than omitting the sample. Such samples intentionally still affect the data scaling process." + ), + "check_sample_weights_invariance": ( + "In LinearBoostClassifier, a zero sample_weight is not equivalent to removing the sample, " + "as samples with zero weight intentionally still affect the data scaling process." ) }, } From d3af90d53bfdb521a41e48fadd53bb471b6b105b Mon Sep 17 00:00:00 2001 From: Hamidreza Keshavarz <32555614+hamidkm9@users.noreply.github.com> Date: Sun, 25 May 2025 21:25:52 +0200 Subject: [PATCH 29/29] Update linear_boost.py --- src/linearboost/linear_boost.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/linearboost/linear_boost.py b/src/linearboost/linear_boost.py index 04f44ed..2dd9bed 100644 --- a/src/linearboost/linear_boost.py +++ b/src/linearboost/linear_boost.py @@ -245,7 +245,7 @@ def _more_tags(self) -> dict[str, bool]: "check_sample_weights_invariance": ( "In LinearBoostClassifier, a zero sample_weight is not equivalent to removing the sample, " "as samples with zero weight intentionally still affect the data scaling process." - ) + ), }, }