The logistic regression and neuralnetwork methods with sensitivity analysis have been evaluated for the effectiveness of theclassification. The classification accuracy is used to measure the performance of both themodels. From the experimental results it is confirmed that the neural network model with...
clf1 = LogisticRegression(solver='lbfgs', multi_class='multinomial', random_state=1) clf2 = RandomForestClassifier(n_estimators=50, random_state=1) clf3 = GaussianNB() ensemble_clf = VotingClassifier(estimators=[('lr', clf1), ('rf', clf2), ('gnb',clf3)], voting='hard')forclf, l...
(X_scaled, iris.target, test_size=0.3, random_state=42) # 训练逻辑回归模型 model = LogisticRegression(max_iter=200) model.fit(X_train, y_train) # 预测测试集结果 y_pred = model.predict(X_test) # 计算准确率 accuracy = accuracy_score(y_test, y_pred) print(f"模型准确率:{accuracy:....
y_pred_sklearn = clf_sklearn.predict(X_test)# h2oclf_h2o = h2o4gpu.LogisticRegression() clf_h2o.fit(X_train, y_train) y_pred_h2o = clf_h2o.predict(X_test)assertnp.allclose(accuracy_score(y_test, y_pred_sklearn), accuracy_score(y_test, y_pred_h2o.squeeze())) 開發者ID:h2oai,...
開發者ID:IBM,項目名稱:differential-privacy-library,代碼行數:27,代碼來源:test_LogisticRegression.py 示例2: test_same_results ▲點讚 6▼ # 需要導入模塊: from sklearn import datasets [as 別名]# 或者: from sklearn.datasets importload_iris[as 別名]deftest_same_results(self):fromsklearnimportdata...
When facing multitask-learning problems, it is desirable that the learning method could find the correct input-output features and share the commonality among multiple domains and also scale-up for large multitask datasets. We introduce the multitask coupled logistic regression (LR) framework called...
吴恩达深度学习系列课程Logistic Regression with a Neural Network mindset中用到的datasets和lr_utils.py文件 lr_utils2018-03-04 上传大小:2.00MB 所需:44积分/C币 吴恩达deeplearning课程作业及需要的的数据包 lr-utils和datasets 吴恩达的深度学习课程是全球范围内非常受欢迎的在线教育项目,旨在教授学员如何构建和理...
vii) Logistic Regression --> Logistic regression is a supervised machine learning algorithm mainly used for classification tasks where the goal is to predict the probability that an instance of belonging to a given class or not. --> It is a kind of statistical algorithm, which analyze the re...
Use the following steps to view component outputs: Right-click the component in the canvas whose output you'd like to see. Select Visualize. Use the samples as starting points for some of the most common machine learning scenarios.Regression...
Code Issues Pull requests This is an EDA and Logistic regression to predict whether a customer will churn. data-analysis machine-learning-datasets Updated Mar 5, 2023 Jupyter Notebook irthomasthomas / Training-Data-For-Instagram-Machine-Learning-Random-Forest-Classifier Sponsor Star 0 Code Iss...