Finally, a support vector machine (SVM) model is constructed for fault classification. The method is tested on seven typical faults of the ASHRAE 1043-RP water chiller dataset and three typical faults of an air-cooled self-built air conditioner simulation dataset. The results show that the ...
我正在尝试使用scikit的递归特征消除和交叉验证来处理具有二进制类问题的(5000, 37)数据,每当我适合该模型时,算法就会进入无限循环。我的数据是: from sklearn.svm import SVC from, 37)) Y = np.random.choice([0, 1], size=(37,)) 我尝试通过以下方式选择< 浏览39提问于2020-11-29得票数 0 回答已采...
wait()方法的作用是让当前线程进行等待也就是让线程停止执行，并且wait()方法方是Object里的方法所有的...
The support vector machine (SVM), random forest (RF), XGBoost (XGB), VGG11, ResNet18, and GoogLeNet classifiers are established to distinguish low-... C Lu,Y Xia,J Han,... - 《Scientific Reports》 被引量: 0发表: 2024年 P1315 Decoding microbiome-metabolome interactions: gaining insights...
>>> from sklearn.datasets import make_friedman1 >>> from sklearn.feature_selection import RFECV >>> from sklearn.svm import SVR >>> X, y = make_friedman1(n_samples=50, n_features=10, random_state=0) >>> estimator = SVR(kernel="linear") >>> selector = RFECV(estimator, step=1...
We chose 35 regions of interest based on the social motivation hypothesis to construct the FC matrix and searched for informative features in the complex high-dimensional FC dataset by the SVM-RFE with a stratified-4-fold cross-validation strategy. The selected features were then entered into an...
Using these features, we build classification models with several Machine Learning algorithms, including AdaBoost, Logistic Regression (LR), k-Nearest Neighbors (k-NN), Naive Bayes (NB), Support Vector Machines (SVM), and Decision Trees (DT). Our results show that...
Then the support vector machine recursive feature elimination cross-validation (SVM-RFECV) is used to select among the preselected feature wavebands to obtain the final modeled wavebands, and the Adaptive Boosting (AdaBoost), Gradient Boosting Decision Tree (GBDT), Random Forest (RF), and Partial...
这是我写的代码当我们在使用Python进行数值计算时，有时会遇到类似于ValueError: cannot convert ...
这是我的代码：1.将数据集分成训练数据集合测试数据集 2.将训练数据集进行归一化 3.使用训练数据集...