从加载的arff文件创建训练和测试变量

Question

I want perform multilabel classification. A have a dataset in arff format which I load. However I don't now how convert import data to X and y vectors in order to apply sklearn/train_test_split.

How can I get X and y?

data, meta = scipy.io.arff.loadarff('../yeast-train.arff')
df = pd.DataFrame(data)

#Get X, y
X, y = ??? <---

X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2)

Answer 1

Ok. Its a multilabel data in which features are in the columns Att1, Att2, Att3.... Att20 and targets are in the columns Class1, Class2, .... Class14 .

So you need to use those columns for getting the X and y. Do it like this:

# Fill the .... with all other column names
feature_cols = ['Att1', 'Att2', 'Att3', 'Att4', 'Att5' ....   'Att20']
target_cols = ['Class1', 'Class2', 'Class3', 'Class4', ....   'Class14']

X, y = df[feature_cols], df[target_cols]