Found input variables with inconsistent numbers of samples: ValueError

Question

Today I am trying build ensemble model. Where I am working with iris dataset. In my model I am using LogisticRegression, KNeighborsClassifier, RandomForestClassifier. But when I am going run the program I get ValueError: Found input variables with inconsistent numbers of samples: [10, 150] error. Below I am giving my code:

df = pd.read_csv('/kaggle/input/iriscsv/Iris.csv')
df.head()
df

output --->

Then I am deleting id collumn from this dataset

df = df.iloc[:, 1:]

After this I am used LabelEncoder on Species column

df['Species'] = encoder.fit_transform(df['Species'])

import seaborn as sns 
sns.pairplot(df, hue = 'Species')

from sklearn.linear_model import LogisticRegression
from sklearn.neighbors import KNeighborsClassifier
from sklearn.ensemble import RandomForestClassifier
from sklearn.model_selection import cross_val_score


clf1 = LogisticRegression()
clf2 = RandomForestClassifier()
clf3 = KNeighborsClassifier()

estimators = [('lr',clf1),('rf',clf2),('knn',clf3)]


for estimator in estimators:
    x = cross_val_score(estimator[1],x,y,cv=10,scoring='accuracy')
    print(estimator[0],np.round(np.mean(x),2))

After running the last estimator I am getting these error.

Answer 1

In your 2nd last line, you are overwriting the variable x, which previously held your input X data.