Data Science Asked by OptimusPrime on March 22, 2021
When I evaluate the model I seem to be getting a decent RMSE score but when I try to actually see the predictions when I call the model all my values are the same.
xdata = xgboost.DMatrix(X_train, y_train, feature_names=all_vars)
xdata_val = xgboost.DMatrix(X_valid, y_valid, feature_names=all_vars)
xgb_parms['seed'] = random.randint(0,1e9)
model = xgboost.train(xgb_parms, xdata)
model.eval(xdata_val)
ypred = model.predict(xdata_val)
I believe the error is on my last step, what am I doing wrong?
Make sure to pass the model an "objective" parameter and also use "rmse" for the "eval_metric" parameter.
https://github.com/dmlc/xgboost/blob/master/doc/parameter.rst
Answered by bbennett36 on March 22, 2021
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