vowpal_wabbit
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VowpalWabbit
Sklearn adapter function `tovw` does not support unsigned integers in features
Mitigation
A user should use signed integer types and not unsigned integer types when passing to the sklearn adapter functions.
Details
The tovw function uses dump_svmlight_file to convert to a format that can easily construct VW text examples.
This function does not support input of unsigned integers, it requires signed due to the pyx code internally in sklearn.
Fails:
from vowpalwabbit.sklearn import VWRegressor
import numpy as np
import pandas as pd
X = pd.DataFrame({'a': [1]}, dtype='uint32')
y = pd.Series(np.zeros(1))
VWRegressor().fit(X, y)
Succeeds:
from vowpalwabbit.sklearn import VWRegressor
import numpy as np
import pandas as pd
X = pd.DataFrame({'a': [1]}, dtype='int32') # <-----
y = pd.Series(np.zeros(1))
VWRegressor().fit(X, y)
The same input works when passed to SKLearn itself:
from sklearn.linear_model import LinearRegression
import numpy as np
import pandas as pd
X = pd.DataFrame({'a': [1]}, dtype='uint32')
y = pd.Series(np.zeros(1))
LinearRegression().fit(X, y)
To fix this one way is to avoid using the dump_svmlight_file function. It is used currently as a way to easily convert the dataframe to vw text format.
