scikit_learnのExtraTreesRegressorをgridsearchCVでチューニングするときにエラーが起きる

Question

scikit_learnのExtraTreesRegressorをgridsearchCVでチューニングするときにエラーが起きています。

エラーは以下の通りです。
ValueError: Invalid parameter n_estimaters for estimator ExtraTreesRegressor(bootstrap=False, criterion='mse', max_depth=None,
max_features=0.1, max_leaf_nodes=None, min_impurity_decrease=0.0,
min_impurity_split=None, min_samples_leaf=1, min_samples_split=2,
min_weight_fraction_leaf=0.0, n_estimators=10, n_jobs=1,
oob_score=False, random_state=None, verbose=0, warm_start=False). Check the list of available parameters with estimator.get_params().keys().

コード```
import numpy as np                                  
import pandas as pd
from sklearn.model_selection import GridSearchCV    
from sklearn.ensemble import ExtraTreesRegressor
from sklearn.metrics import r2_score
from sklearn.metrics import mean_squared_error
from sklearn.metrics import mean_absolute_error

sample_data = pd.read_csv('transformed_include_error_4.csv')
sample_data = sample_data.query('Error ==0')

sample_data = pd.read_csv('transformed_include_error_4.csv')
test_data = sample_data.query('Error ==0') 

np.random.seed(seed=42)
indices = np.random.permutation(len(sample_data))
train_size = 140
train_idx, test_idx = indices[:train_size], indices[train_size:]

train_data = sample_data.iloc[train_idx]
test_data = test_data.iloc[test_idx]

y_train = train_data['Rate']
x_train = train_data.loc[:,["feature_1","feature_2","feature_3","feature_4"]]

y_test = test_data['Rate']
x_test = test_data.loc[:,["feature_1","feature_2","feature_3","feature_4"]]

params = {
    "n_estimaters":[100],
    "max_features":[0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9],
     "random_state":[42]
}
    
clf = GridSearchCV(
    ExtraTreesRegressor(),
    params,
    cv=10,
    scoring = "r2"
)
clf.fit(x_train,y_train)

Comments

[hayataka2049]

コードとエラーを全文掲載してください。また、コードは<code>ボタンで挿入できるコードブロックの中に書いてください。

Answer 1

誤：n_estimaters
正：n_estimators

Comments

[hizuma]

すみません。恥ずかしいミスでした。
ありがとうございます。