CODEWITHSUNDEEP
pythondatasetscikit-learnsvm
Kratos
Kratos

Reputation: 1114

Turning list to svm input

I am implementing an svm model with python and scikit learn. I have reached to a point where I have selected and transformed my features and merged them to a list that looks like this:

[[17, 14, 14, 7, 14, 14, 14, 7, 14, 14, 1], 
 [14, 14, 7, 14, 14, 14, 7, 14, 14, 7, 1], 
 [14, 7, 14, 14, 14, 7, 14, 14, 7, 14, 1], 
 [7, 14, 14, 14, 7, 14, 14, 7, 14, 7, 1], 
 [14, 14, 14, 7, 14, 14, 7, 14, 7, 14, 1], 
 [14, 14, 7, 14, 14, 7, 14, 7, 14, 7, 1], 
 [14, 7, 14, 14, 7, 14, 7, 14, 7, 13, 1], 
 [7, 14, 14, 7, 14, 7, 14, 7, 13, 7, 1], 
 [14, 14, 7, 14, 7, 14, 7, 13, 7, 14, 1], 
 [14, 7, 14, 7, 14, 7, 13, 7, 14, 10, 1], 
 [7, 14, 7, 14, 7, 13, 7, 14, 10, 4, 1], 
 [14, 7, 14, 7, 13, 7, 14, 10, 4, 13, 1], 
 [7, 14, 7, 13, 7, 14, 10, 4, 13, 13, 1], 
 [14, 7, 13, 7, 14, 10, 4, 13, 13, 7, 1], 
 [7, 13, 7, 14, 10, 4, 13, 13, 7, 13, 1], 
 [13, 7, 14, 10, 4, 13, 13, 7, 13, 3, 1], 
 [7, 14, 10, 4, 13, 13, 7, 13, 3, 13, 1], 
 [14, 10, 4, 13, 13, 7, 13, 3, 13, 13, 1], 
 [10, 4, 13, 13, 7, 13, 3, 13, 13, 3, 1], 
 [4, 13, 13, 7, 13, 3, 13, 13, 3, 13, 0], 
 [13, 13, 7, 13, 3, 13, 13, 3, 13, 13, 0], 
 [13, 7, 13, 3, 13, 13, 3, 13, 13, 14, 0]]

The last number in each tuple is the label. I am trying to find a way to create a dataset that could separate the data and the target in order to build a model. I couldn't find anything similar in the documentation. Will it be easier to turn it back to Dataframe?

Thank you!

Upvotes: 1

Views: 830

Answers (1)

Quan Tran
Quan Tran

Reputation: 426

Do you mean separate the features from the labels? If so, you can use numpy.

from sklearn import svm
import numpy as np
data = np.asarray(A)
X = data[:,:-1]
y = data[:,-1]
clf = svm.SVC()
clf.fit(X, y)

A is the original data list.

Upvotes: 3

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