Of all data problems in linear regression, we are more concerned about the nearly linear dependency among several factors assumed independent implicitly in the model specification. Numerically, high dependency results directly in rank-deficiency problem in the OLS estimation. The resultant problems, such...
)X3=np.column_stack([X1,np.random.rand(100,2)])import matplotlib.pyplot as pltclf=LinearRegression()vif2=np.zeros((10,1))for i in range(10):tmp=[k for k in range(10) if k!=i]clf.fit(X2[:,tmp],X2[:,i])vifi=1/(1-clf.score(X2[:,tmp],X2[:,i]))vif2[i]=vifi ...
get_loc(i)) for i in x.columns] vif 代码语言:javascript 代码运行次数:0 运行 AI代码解释 x_train,x_test,y_train,y_test=train_test_split(x,y,test_size=0.2,random_state=2021) clf=LogisticRegression(max_iter=300) clf.fit(x_train,y_train) y_pred=clf.predict(x_test) accuracy_score(...
1. from sklearn.linear_model import LogisticRegression #导入逻辑回归模型 2. clf = LogisticRegression() 3. print clf 4. clf.fit(train_feature,label) 5. predict['label'] = clf.predict(predict_feature) 1. 2. 3. 4. 5. 输出结果如下: [python] 1. LogisticRegression(C=1.0, class_weight=...
= score model = LinearRegression() # 随机生成1000计算R2的平均值 R2_list = [] for i in ...
import numpy as npfrom sklearn.linear_model import LinearRegressionfrom sklearn import cross_validation coef0=np.array([5,6,7,8,9,10,11,12]) X1=np.random.rand(100,8) y=np.dot(X1,coef0)+np.random.normal(0,1.5,size=100) training=np.random.choice([True,False],p=[0.8,0.2],size=...
# 画图import seaborn as sns# 制作数据集from sklearn.datasets import make_blobs# VIF膨胀因子from statsmodels.stats.outliers_influence import variance_inflation_factor# 分割数据集from sklearn.model_selection import train_test_split# 逻辑回归from sklearn.linear_model import LogisticRegression# AUC和准确度...
# 画图importseabornassns# 制作数据集fromsklearn.datasetsimportmake_blobs# VIF膨胀因子fromstatsmodels.stats.outliers_influenceimportvariance_inflation_factor# 分割数据集fromsklearn.model_selectionimporttrain_test_split# 逻辑回归fromsklearn.linear_modelimportLogisticRegression# AUC和准确度fromsklearn.metricsimpor...
In ordinary least square (OLS) regression analysis, multicollinearity exists when two or more of theindependent variablesdemonstrate a linear relationship between them. For example, to analyze the relationship of company sizes and revenues to stock prices in a regression model, market capitalizations and...
ENR是一套完整的数据处理、计算和制图软件系统。其功能包括：数据存储和处理系统；数组运算工具（其向量...