问题
I would like to use an Attribute-Relation File Format with scikit-learn to do some NLP task, is this possible? How can use an .arff
file with scikit-learn
?
回答1:
I really recommend liac-arff. It doesn't load directly to numpy, but the conversion is simple:
import arff, numpy as np
dataset = arff.load(open('mydataset.arff', 'rb'))
data = np.array(dataset['data'])
回答2:
I found that scipy has a loader for arff files to load them as numpy record arrays. I am not 100% sure that those arrays are suitable for direct consumption by scikit-learn but that should get your started.
回答3:
Follow renatopp's answer: assume your data is the iris dataset, there should be 5 dimensional with last one is the class label column.
s = svm.SVC()
data_input = data[:,0:4]
labels = data[:,4] # this is the class column
s.fit(data_input, labels)
I think this is something you want.
回答4:
If your "arff" file is a text file, try the following code instead:
import arff, numpy as np
dataset = arff.loads(open('mydataset.arff', 'rt'))
data = np.array(dataset['data'])
来源:https://stackoverflow.com/questions/27264426/arff-files-with-scikit-learn