版权声明：本文为博主原创文章，未经博主允许不得转载。 https://blog.csdn.net/qq_36556893/article/details/82852599
一、遇到的问题
博主在做随机森林的学习运行代码出现一下错误：
from sklearn.datasets import load_iris
from sklearn.ensemble import RandomForestClassifier
import pandas as pd
import numpy as np
iris = load_iris()
df = pd.DataFrame(iris.data, columns=iris.feature_names)
df['is_train'] = np.random.uniform(0, 1, len(df)) <= .75
df['species'] = pd.Factor(iris.target, iris.target_names)
df.head()
train, test = df[df['is_train']==True], df[df['is_train']==False]
features = df.columns[:4]
clf = RandomForestClassifier(n_jobs=2)
y, _ = pd.factorize(train['species'])
clf.fit(train[features], y)
preds = iris.target_names[clf.predict(test[features])]
pd.crosstab(test['species'], preds, rownames=['actual'], colnames=['preds'])File "test_iris_with_rf.py", line 9, in <module>
df['species'] = pd.Factor(iris.target, iris.target_names)
AttributeError: 'module' object has no attribute 'Factor'后来发现这是因为pandas版本太新了...
二、解决方法
将
pd.Factor(iris.target, iris.target_names)改为
pd.Categorical.from_codes(iris.target, iris.target_names)这样就没问题了~