# 需要导入模块: from sklearn import multioutput [as 别名]# 或者: from sklearn.multioutput importMultiOutputRegressor[as 别名]deftest_multi_target_regression_partial_fit():X, y = datasets.make_regression(n_targets=3) X_train, y_train = X[:50], y[:50] X_test, y_test = X[50:], ...
核心代码: # from sklearn.linear_model import LogisticRegressionfromsklearn.multioutputimportMultiOutputClassifierfromsklearn.naive_bayesimportMultinomialNBfromutils.data_utilimportload_pickleimportosfrompathConfigimportdata_dirfromutils.vocab_utilimportvocab_to_index_dictimportnumpyasnp# train & test datatrain...
This section covers two modules:sklearn.multiclassandsklearn.multioutput. The chart below demonstrates the problem types that each module is responsible for, and the corresponding meta-estimators that each module provides. 模型分类特征表: 前面三个都是面向离散目标(分类), 最后一个面向连续型/数值型目...
Inherently multiclass:Naive Bayes,LDA and QDA,Decision Trees,Random Forests,Nearest Neighbors, settingmulti_class='multinomial'insklearn.linear_model.LogisticRegression. Support multilabel:Decision Trees,Random Forests,Nearest Neighbors,Ridge Regression. One-Vs-One:sklearn.svm.SVC. One-Vs-All: all lin...
<ipython-input-46-1c4d4ebecc3f>in<module>()1# Select a linear---> 2 from sklearn import linear_modelC:\Users\Usuario\Anaconda3\lib\site-packages\sklearn\linear_model__init__.pyin<module>()1314from.bayesimportBayesianRidge, ARDRegression---> 15 from .least_angle import (Lars, LassoLars...
datasets import make_regression from sklearn.svm import LinearSVR # create datasets X, y = make_regression(n_samples=1000, n_features=10, n_informative=5, n_targets=2, random_state=1) # define model model = LinearSVR() # fit model # (THIS WILL CAUSE AN ERROR!) model.fit(X, y) ...
fromsklearn.multioutputimportMultiOutputClassifierfromsklearn.linear_modelimportLogisticRegressionclf=Multi...
sklearn.discriminant_analysis.LinearDiscriminantAnalysis sklearn.svm.LinearSVC (setting multi_class=”crammer_singer”) sklearn.linear_model.LogisticRegression (setting multi_class=”multinomial”) sklearn.linear_model.LogisticRegressionCV (setting multi_class=”multinomial”) ...
from sklearn.linear_modelimportLogisticRegressionunique_origins=cars["origin"].unique()unique_origins.sort()models={}features=[cforcintrain.columnsifc.startswith("cyl")or c.startswith("year")]fororigininunique_origins:model=LogisticRegression()X_train=train[features]y_train=train["origin"]==orig...
# 需要导入模块: from sklearn import linear_model [as 别名]# 或者: from sklearn.linear_model importMultiTaskLasso[as 别名]deftest_model_multi_task_lasso(self):model, X = fit_regression_model(linear_model.MultiTaskLasso(), n_targets=2) ...