Python实现Stacking分类模型(RandomForestClassifier、ExtraTreesClassifier、AdaBoostClassifier、GradientBoostingClassifier、SVC)项目实战
x = data.drop(["Survived"],inplace = False,axis = 1) xtrain,xtest,ytrain,ytest = train_test_split(x,y,test_size=0.3) #调整索引: for i in [xtrain,xtest,ytrain,ytest]: i.index = range(i.shape[0]) x.head() 1. 2. 3. 4. 5. 6. 7. 4 模型建立 clf = DecisionTreeCl...
KNeighborsClassifier(3), SVC(probability=True), DecisionTreeClassifier(), RandomForestClassifier(), AdaBoostClassifier(), GradientBoostingClassifier(), GaussianNB(), LinearDiscriminantAnalysis(), QuadraticDiscriminantAnalysis(), LogisticRegression()] log_cols = ["Classifier", "Accuracy"] log = pd.DataF...
滚动轴承状态监测与故障诊断 | 本项目采用Python编程语言,jupyter notebook文本编辑器,使用的部分模块如下: import matplotlib.pyplot as plt import numpy as np import pandas as pd import seaborn as sns from sklearn.neural_network import MLPClassifier from sklearn.neighbors import KNeighborsClassifier from s...
根据前面的公式推导,支持向量分类器和SMO算法已经用Python代码实现,链接:Models/SupportVectorMachine · ThE_eXpLoReR/MELON - 码云 - 开源中国 原笔记地址链接: Notes/SupportVectorMachine/SupportVectorClassifier.md · ThE_eXpLoReR/MELON - 码云 - 开源中国 关于支持向量回归器(SVR)和SMO算法求解的推导在下一篇文...
clf=svm.SVC(kernel='rbf') result=[] for i in range(5): x_train,x_test,y_train,y_test=cross_validation.train_test_split(x,y,test_size=0.2) clf.fit(x_train,y_train) result.append(np.mean(y_test==clf.predict(x_test))) print("svm classifier accuacy:") print(result)上...
python machine-learning facebook machine-learning-algorithms gradient-boosting-classifier svc personality-traits big5 liwc random-forest-classifier liwc-dictionaries linear-regression-classification sgd-classifier personality-predicting multinomialnb facebook-status-scraper big5-ocean-traits logistic-regression-classifi...
print("Fitting the classifier to the training set") t0=time() param_grid={'C': [1e3,5e3,1e4,5e4,1e5], 'gamma': [0.0001,0.0005,0.001,0.005,0.01,0.1], } clf=GridSearchCV(SVC(kernel='rbf', class_weight='balanced'), param_grid) ...
OpenCV中ORB特征提取与匹配 FAST特征点定位 ORB - (Oriented Fast and Rotated BRIEF)算法是基于FAST...
pythonadaboost调参 在做数据处理时,需要用到不同的手法,如特征标准化,主成分分析,等等会重复用到某些参数,sklearn中提供了管道,可以一次性的解决该问题先展示先通常的做法 import pandas as pd from sklearn.preprocessing import StandardScaler from sklearn.decomposition import PCA from skl ...