Splet06. mar. 2024 · As you can see, we got the error that clearly says that the SMOTE object does not have a fit_sample attribute. Let us now go through some of the possible … Splet1、 引言. 与 scikit-learn相似依然遵循这样的代码形式进行训练模型与采样数据. Data：是二维形式的输入 targets是一维形式的输入. 不平衡数据集的问题会影响机器学习算法的学习阶段和后续的预测。. 平衡问题对应于不同类中样本数量的差异。. 如下图所示，当不 ...

AttributeError:

SpletParameters. sampling_strategyfloat, str, dict or callable, default=’auto’. Sampling information to resample the data set. When float, it corresponds to the desired ratio of … Splet06. mar. 2024 · As you can see, there are very few elements from the second category which means the dataset is highly imbalanced. In order to make the data balanced, we will apply the SMOTE method in order to increase the … fiona homepage

AttributeError: ‘SMOTE’ object has no attribute ‘fit_sample ...

Spletfit_sample(X, y) [source] Fit the statistics and resample the data directly. get_params(deep=True) [source] Get parameters for this estimator. sample(X, y) [source] Resample the dataset. set_params(**params) [source] Set the parameters of this estimator. The method works on simple estimators as well as on nested objects (such as pipelines). SpletThe base AdaBoost classifier used in the inner ensemble. Note that you can set the number of inner learner by passing your own instance. New in version 0.10. When set to True, reuse the solution of the previous call to fit and add more estimators to the ensemble, otherwise, just fit a whole new ensemble. Splet16. jan. 2024 · Next, we can oversample the minority class using SMOTE and plot the transformed dataset. We can use the SMOTE implementation provided by the imbalanced-learn Python library in the SMOTE class.. The SMOTE class acts like a data transform object from scikit-learn in that it must be defined and configured, fit on a dataset, then applied … fiona hood stewart books