`ValueError: The Least Populated Class In Y Has Only 1 Member, Which Is Too Few` In PyCaret

- 1 answer

I have a problem, working with PyCaret. Previously I did not have any problems.

But it started when I oversampled data and saved it, using pandas and this question.

The file is here.

Then I read the file in a separate notebook.

import pycaret
from pycaret.utils import version
from pycaret.regression import *
from pycaret.classification import *

# Read clean data
starbucks_days = pd.read_csv('days_smote.csv')

# Drop a column
starbucks_days = starbucks_days.drop(['Unnamed: 0'], axis = 1)
starbucks_days = starbucks_days.drop(['transaction', 'offer_viewed', 'offer_received', 'offer_completed'], axis = 1)
starbucks_days = starbucks_days.drop(['label'], axis = 1)

The I start to use PyCaret

# Initialize Setup
starbucks_days1 = setup(starbucks_days, target = 'time_completed_viewed', session_id = 123, log_experiment = True, experiment_name = 'days1')

But get an error

ValueError: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.

This GitHub issue gives some hints

I check some parameters


6.000000      1682
12.000000     1503
18.000000     1318
24.000000     1212
174.000000    1068
444.107530       1
226.213225       1
411.947513       1
236.001744       1
394.722944       1
Name: time_completed_viewed, Length: 3572, dtype: int64

Any tips what am I missing? As I said, PyCaret works just fine with simple csv files, which were not oversampled.



In your imports, you have imported classification after importing regression that has overwritten the module in the environment.

This seems like a regression problem (continuous value). You don't need to import classification.

Get rid of this line from your code and it should work fine:

from pycaret.classification import *