def __test_tp1_task2():
np.random.seed(50)
X, Y_ = data.sample_gmm(6, 2, 10)
W1, b1, W2, b2 = fcann2_train(X, Y_, param_hidden_len=100)
decfunc = fcann2_classify_new(W1, b1, W2, b2)
Y = np.argmax(fcann2_classify(X, W1, b1, W2, b2), axis=1)
bbox = (np.min(X, axis=0), np.max(X, axis=0))
data.graph_surface(decfunc, bbox, offset=0.5)
data.graph_data(X, Y_, Y)
plt.show()
def __test():
np.random.seed(100)
X, Y_ = data.sample_gmm(6, 2, 10)
svm = KSVMWrap(X, Y_)
Y = svm.predict(X)
accuracy, recall, precision = data.eval_perf_binary(Y, Y_)
print("Accuracy : ", accuracy)
print("Precision : ", precision)
print("Recall : ", recall)
bbox = (np.min(X, axis=0), np.max(X, axis=0))
data.graph_surface(svm.get_scores, bbox, offset=0)
data.graph_data(X, Y_, Y, special=svm.support())
plt.show()
self.clf = self.clf.fit(X, Y_)
self.support = self.clf.support_ #Indeksi podataka koji su odabrani za potporne vektore
self.Y_ = Y_
def predict(self, X):
return self.clf.predict(X)
def get_scores(self, X):
return classification_report(self.Y_, self.predict(X))
if __name__ == "__main__":
# inicijaliziraj generatore slučajnih brojeva
np.random.seed(100)
#X,Y_ = data.sample_gmm(4, 2, 40)
X, Y_ = data.sample_gmm(6, 2, 10)
Yoh_ = data.class_to_onehot(Y_)
svm2 = KSVMWrap(X, Y_)
print(svm2.get_scores(X))
bbox = (np.min(X, axis=0), np.max(X, axis=0))
data.graph_surface(svm2.predict, bbox, offset=0.5, width=256, height=256)
data.graph_data(X, Y_, svm2.predict(X), special=svm2.support)
plt.show()
def logreg_classify(X, W, b):
return output(X, W, b)
def logreg_decfun(w, b):
def classify(X):
return logreg_classify(X, w, b)
return classify
if __name__ == "__main__":
np.random.seed(100)
# get the training dataset
X, Y_ = data.sample_gmm(5, 2, 100)
# train the model
W, b = logreg_train(X, Y_)
# evaluate the model on the training dataset
probs, logprobs = logreg_classify(X, W, b)
Y = np.argmax(probs, axis=1)
# report performance
accuracy, confusion_matrix, recall = data.eval_perf_multi(Y, Y_)
print(accuracy, confusion_matrix, recall)
data.graph_data(X, Y_, Y, special=[])
decfun = logreg_decfun(W, b)