I do not understand the problem.
Challenge - Diabetes Classification
Hey @Abhishek-Vishwakarma-653004358467067, in this problem we are given Diabetes data consisting of the following features :
['Pregnancies', 'Glucose', 'BloodPressure', 'SkinThickness', 'Insulin', 'BMI', 'DiabetesPedigreeFunction', 'Age', 'Outcome']
Based on these features, you need to predict whether the person is suffering from diabetes or not. The outcome column, is your y_train and the rest of the 8 features can be your x_train. You need to use KNN algorithm to make predictions on the test data.
I hope this gives you a better insight into the problem.
All the best 
so, what is the use of Diabetes_Xtest.csv and sample_submission.csv?
Once you have built your model, then you will make predictions on the testing data. That testing data is given in the Diabetes_Xtest.csv file. And sample_submission.csv is just for your reference to see that in what format you need to prepare your final csv file that contains the predictions made by your KNN model on the testing data.
Happy Learning
means I have to apply KNN on Diabetes_XTrain.csv(X) and Diabetes_Xtest.csv(Z). like:
knn(X,Y,Z[j],k=5)
where, Y is Diabetes_YTrain.csv
could you explain steps?
I would suggest you to first go through the videos of KNN in the course. Then you can implement the algorithm on this dataset. Try implementing it on your own even if you feel it’s wrong , it’s okay. You can raise a new doubt if you get any type of errors or are stuck at any conceptual problem.
In the end if you are not able to do anything , then you can take help from this link.
But make sure you first try it on your own.
All the best
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