机器学习笔记（不定时更新）

pandas 函数

pandas.get_dummies()
对one-hot编码

#以kaggle titanic 里面的片段为例
features = ["Pclass", "Sex", "SibSp", "Parch"]
X = pd.get_dummies(train_data[features])
print(X)

pandas.DataFrame() 可以用字典方式创建

output = pd.DataFrame({'PassengerId': test_data.PassengerId, 'Survived': predictions})

sklearn函数

RandomForestClassifier 随机决策树

>>> from sklearn.ensemble import RandomForestClassifier
>>> X = [[0, 0], [1, 1]]
>>> Y = [0, 1]
>>> clf = RandomForestClassifier(n_estimators=10)
>>> clf = clf.fit(X, Y)

标签：features,RandomForestClassifier,clf,更新,笔记,pd,定时,pandas,dummies
来源： https://blog.csdn.net/LTuantuan/article/details/113620531