<code>import numpy as np
import pandas as pd
df = pd.read_csv('C:/Users/sayed/Downloads/placement.csv')
df = df.iloc[:, 1:]
X = df.iloc[:, 0:2]
Y = df.iloc[:,-1]
from sklearn.model_selection import train_test_split
x_train, x_test, y_train, y_test = train_test_split(X, Y, test_size=0.1)
from sklearn.preprocessing import StandardScaler
scaler = StandardScaler()
x_train = scaler.fit_transform(x_train)
x_test = scaler.transform(x_test)
</code>
<code>import numpy as np
import pandas as pd
df = pd.read_csv('C:/Users/sayed/Downloads/placement.csv')
df = df.iloc[:, 1:]
X = df.iloc[:, 0:2]
Y = df.iloc[:,-1]
from sklearn.model_selection import train_test_split
x_train, x_test, y_train, y_test = train_test_split(X, Y, test_size=0.1)
from sklearn.preprocessing import StandardScaler
scaler = StandardScaler()
x_train = scaler.fit_transform(x_train)
x_test = scaler.transform(x_test)
</code>
import numpy as np
import pandas as pd
df = pd.read_csv('C:/Users/sayed/Downloads/placement.csv')
df = df.iloc[:, 1:]
X = df.iloc[:, 0:2]
Y = df.iloc[:,-1]
from sklearn.model_selection import train_test_split
x_train, x_test, y_train, y_test = train_test_split(X, Y, test_size=0.1)
from sklearn.preprocessing import StandardScaler
scaler = StandardScaler()
x_train = scaler.fit_transform(x_train)
x_test = scaler.transform(x_test)
After performing the x_test = scaler.transform(x_test) I am getting this warning
UserWarning: X does not have valid feature names, but StandardScaler was fitted with feature names warnings.warn(
I did ask this to ChatGPT, this is what it gave
The warning you’re getting is due to a mismatch in how the scaler was fitted and how it’s being used
I am still unclear about the error.