PROSAGA码农传奇-数据防泄漏-防止随机森林回归器中数据泄漏的建议

防止随机森林回归器中数据泄漏的建议

作者: 春风助手
发布时间: 2025-02-22 09:10:25 (4天前)

我目前的精度和f1测量值都为1.00。我怀疑这是数据泄漏的结果。我正在寻找尽可能减少数据泄漏的任何技巧。谢谢。这是我的python脚本：
<pre><code>import pandas as pd 
import numpy as np 
# Other imports here
from sklearn.ensemble import RandomForestRegressor
from sklearn.metrics import classification_report
from sklearn.metrics import accuracy_score
from sklearn.model_selection import train_test_split
dataset = pd.read_csv("weather.csv")

print(len(dataset))

dataset = pd.get_dummies(dataset, columns=["Date", "Location", "WindGustDir", "WindDir9am", "WindDir3pm",])

dataset["RainToday"] = dataset["RainToday"].map({'Yes': 1, 'No': 0})
dataset["RainTomorrow"] = dataset["RainTomorrow"].map({'Yes': 1, 'No': 0})

dataset.dropna(inplace=True)

dataset = dataset.rename_axis(None)

X = dataset.drop('RainTomorrow', axis=1)

y = dataset['RainTomorrow']

X_train, X_test, y_train, y_test = train_test_split(X,y,test_size=0.20, random_state=216037514)

classifier = RandomForestRegressor(n_estimators = 200, random_state = 216037514)
classifier.fit(X_train,y_train)

y_pred = classifier.predict(X_test)

print("Report:\n", classification_report(y_test,y_pred))
print("Accuracy: ", accuracy_score(y_test,y_pred))
</code></pre>当前结果：
<pre><code>142193
Report:
 precision recall f1-score support

0       1.00      1.00      1.00      9026
           1       1.00      1.00      1.00      2592

micro avg       1.00      1.00      1.00     11618
   macro avg       1.00      1.00      1.00     11618
weighted avg       1.00      1.00      1.00     11618

Accuracy: 1.0
</code></pre>