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When I run a linear regression, my code is as follows: all_features = df_vaex.column_names[2:96]+df_vaex.column_names[99:173]+df_vaex.column_names[181:] target = 'excess_ret' model = LinearRegression() vaex_model = Predictor(features=all_features, target=target, model=model) vaex_model.fit(df_train)
When I run the model coefficients, this code is valid: vaex_model.model.coef_
But when I want to calculate the R-square on the test dataset, I run this code: vaex_model.transform(df_test)
And now there is an error: "Column or variable 'm' does not exist. Did you mean: 'ms' or 'bm'". But I have checked my dataset and ensure that there is no column or variable named 'm'. Is this the Vaex's bug?
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When I run a linear regression, my code is as follows:
all_features = df_vaex.column_names[2:96]+df_vaex.column_names[99:173]+df_vaex.column_names[181:]
target = 'excess_ret'
model = LinearRegression()
vaex_model = Predictor(features=all_features, target=target, model=model)
vaex_model.fit(df_train)
When I run the model coefficients, this code is valid:
vaex_model.model.coef_
But when I want to calculate the R-square on the test dataset, I run this code:
vaex_model.transform(df_test)
And now there is an error: "Column or variable 'm' does not exist. Did you mean: 'ms' or 'bm'". But I have checked my dataset and ensure that there is no column or variable named 'm'. Is this the Vaex's bug?
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