我试图运行此代码:(信用转到Greg)
import pandas as pd
from sklearn.cross_validation import train_test_split
import statsmodels.api as sm
quality = pd.read_csv("https://courses.edx.org/c4x/MITx/15.071x/asset/quality.csv")
train, test = train_test_split(quality, train_size=0.75, random_state=1)
qualityTrain = pd.DataFrame(train, columns=quality.columns)
qualityTest = pd.DataFrame(test, columns=quality.columns)
qualityTrain['PoorCare'] = qualityTrain['PoorCare'].astype(int)
cols = ['OfficeVisits', 'Narcotics']
x = qualityTrain[cols]
x = sm.add_constant(x)
y = qualityTrain['PoorCare']
model = sm.Logit(y, x).fit()
model.summary()
但我得到了:
AttributeError: 'int' object has no attribute 'exp'
在倒数第二行。通过对数据进行采样(train_test_split)可以明确地介绍这一点,因为该模型适用于整个未修改的数据集。
如何解决这个问题?
答案 0 :(得分:6)
只需将x变量转换为浮点数:
model = sm.Logit(y, x.astype(float)).fit()
我得到以下结果:
<class 'statsmodels.iolib.summary.Summary'>
"""
Logit Regression Results
==============================================================================
Dep. Variable: PoorCare No. Observations: 98
Model: Logit Df Residuals: 95
Method: MLE Df Model: 2
Date: Mon, 23 Mar 2015 Pseudo R-squ.: 0.2390
Time: 16:45:51 Log-Likelihood: -39.714
converged: True LL-Null: -52.188
LLR p-value: 3.823e-06
================================================================================
coef std err z P>|z| [95.0% Conf. Int.]
--------------------------------------------------------------------------------
const -2.7718 0.561 -4.940 0.000 -3.872 -1.672
OfficeVisits 0.0680 0.031 2.211 0.027 0.008 0.128
Narcotics 0.1223 0.041 2.991 0.003 0.042 0.203
================================================================================
"""