更新:Yellowbrick API现在使用viz.show
而不是viz.poof
。
Yellowbrick将matplotlib封装起来以生成可视化效果,因此您可以通过直接调用matplotlib来影响图形的所有可视设置。我发现最简单的方法是通过访问Visualizer.ax
属性并在那里直接设置内容,当然,您也可以直接使用plt
来管理全局图形。
下面是一些生成类似于您示例的代码:
import pandas as pd
from yellowbrick.classifier import ConfusionMatrix
from sklearn.ensemble import AdaBoostClassifier
from sklearn.model_selection import train_test_split as tts
data = pd.read_csv('examples/data/occupancy/occupancy.csv')
features = ["temperature", "relative humidity", "light", "C02", "humidity"]
# Extract the numpy arrays from the data frame
X = data[features].as_matrix()
y = data.occupancy.as_matrix()
X_train, X_test, y_train, y_test = tts(X, y, test_size=0.2)
clf = AdaBoostClassifier()
viz = ConfusionMatrix(clf)
viz.fit(X_train, y_train)
viz.score(X_test, y_test)
viz.show()
您可以按照以下方式在score
和show
之间开始管理图形:
viz.fit(X_train, y_train)
viz.score(X_test, y_test)
for label in viz.ax.texts:
label.set_size(12)
viz.show()