Hi,

I am trying to apply logistic regression on the human activity regression data. It consists of 6 levels of outcome describing different activities, After applying PCA on train and test combined data(continuous variables only) I ended up with 150 principal components from 562 variables. Now I am trying to apply logistic regression for classification using :

`from sklearn import linear_model clf=linear_model.LogisticRegression(C=1e5) clf.fit(train_x,train.activity)`

In the above code `train_x`

consists of the 150 proncipal components and `train.activity`

is the outcome. After predicting it on test data set using :

`clf.predict(test_x)`

I am getting an array with minimum value of 1 and max value of 6. If there were two outcomes, I would have tried to find a suitable threshold to classify, But here there are 6 outcomes. Please suggest a way to apply logistic regression to classify on 6 possible outcomes.

Thanks in advance

Danish