SVM solution for the Dogs vs. Cats competition

sol_03_svm

# Build model
import sklearn
from sklearn.cross_validation import train_test_split
from sklearn.grid_search import GridSearchCV
from sklearn.svm import LinearSVC

X_train, y_train = svm_features.reshape(300,7*7*512), svm_labels

param = [{
          "C": [0.01, 0.1, 1, 10, 100]
         }]
 
svm = LinearSVC(penalty='l2', loss='squared_hinge')  # As in Tang (2013)
clf = GridSearchCV(svm, param, cv=10)
clf.fit(X_train, y_train)