Danishtah Quamar

In seaborn.regplot, x and y refers to the column names in data. So the statement in your code is expecting data.

Try the code below:

sns.regplot(np.array(Y_test), model.predict(X_test))

plt.show()

The error message you are encountering suggests that you need to pass a DataFrame or array-like object to the data parameter of sns.regplot when using named variables for x and y. In your case, you can create a DataFrame or use numpy arrays to plot the scatter and fitting line. Here's how you can do it:

Assuming you have Y_test and the predicted values in y_pred, you can create a DataFrame using pandas:

import pandas as pd

import numpy as np

import seaborn as sns

import matplotlib.pyplot as plt

# Assuming you have Y_test and y_pred

Y_test = np.array([1, 2, 3, 4, 5])

y_pred = np.array([1.2, 2.1, 2.9, 4.2, 4.8])

# Create a DataFrame

data = pd.DataFrame({'Y_test': Y_test, 'y_pred': y_pred})

# Plot scatter plot with fitting line

sns.regplot(x='Y_test', y='y_pred', data=data)

plt.show()

If you don't have pandas available and you want to use numpy arrays directly, you can do the following:

import numpy as np

import seaborn as sns

import matplotlib.pyplot as plt

# Assuming you have Y_test and y_pred as numpy arrays

Y_test = np.array([1, 2, 3, 4, 5])

y_pred = np.array([1.2, 2.1, 2.9, 4.2, 4.8])

# Plot scatter plot with fitting line

sns.regplot(x=Y_test, y=y_pred)

plt.show()

Both of the above examples will generate a scatter plot with a

fitting line between the actual values (Y_test) and

the predicted values (y_pred). Make sure to adjust the data

accordingly to match your actual data.

Thank you. This is helpful.

Sulaf Waiss