Oh right! Take out the species in the features array. That should fix the "ValueError: could not convert string to float: 'setosa'"
species
Also, I've added the missing from sklearn.metrics import mean_absolute_error for the mean_absolute_error function.
from sklearn.metrics import mean_absolute_error
mean_absolute_error
Here's a link to a working kaggle notebook: kaggle.com/interestedmike/iris-dat...
Are you sure you want to hide this comment? It will become hidden in your post, but will still be visible via the comment's permalink.
Hide child comments as well
Confirm
For further actions, you may consider blocking this person and/or reporting abuse
We're a place where coders share, stay up-to-date and grow their careers.
Oh right! Take out the
speciesin the features array. That should fix the "ValueError: could not convert string to float: 'setosa'"Also, I've added the missing
from sklearn.metrics import mean_absolute_errorfor the
mean_absolute_errorfunction.Here's a link to a working kaggle notebook: kaggle.com/interestedmike/iris-dat...