随机森林模型训练和预测
from sklearn.ensembleimport RandomForestRegressorfrom sklearn.metrics import mean_absolute_errorfrom sklearn.model_selection import train_test_splitmodel =RandomForestRegressor(n_estimators=2900,min_s
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from sklearn.ensemble import RandomForestRegressor
from sklearn.metrics import mean_absolute_error
from sklearn.model_selection import train_test_split
model =RandomForestRegressor(n_estimators=2900,min_samples_leaf=1,max_features="sqrt")
X_train,X_test,y_train,y_test = train_test_split(X,y,test_size=0.4,random_state=0)
model.fit(X_train,y_train)
y_pred = model.predict(X_test)
mean_absolute_error(y_true=y_test,y_pred=y_pred)
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