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I try to pass the ML Practitioner Certificate. I follow the Hands-on Instructions, but after splitting my original dataset into two smaller ones (train_data and validation_data), and after creating a baseline ML model applied to the train_data, I find out that both models (random forest and logistic regression) show a score of 1.
I wonder how this is possible. I retried multiple times, still the same. I followed every step mentioned previously. The only data preprocessing I did is to change the type of the columns of the school_data as mentioned in the previous steps.
Any idea ?
Thanks in advance.
Thanks for your response @phh .
That makes sense. I disabled the grade feature and tried again, and the score is lower (around 0.9). But the thing is, as the Hands-on Instructions suggest, I should face some diagnostic issues. That's not the case here. I have a score of 0.922, with no diagnostic issue at all.
I feel like something is wrong.
Same here, I cannot see any issue in the Diagnostics. After using the design specs also I get the same results. I removed 'grade' column. Also how to deploy this model? I do not see any option for 'deploy model'. Please help me.