def fit(self, X, Y):
[Y_new, self.old_to_new, self.new_to_old,
num_class] = target_process.translate(Y)
self.classifier = pysol.SOL('ogd', num_class, **self.params)
self.classifier.fit(X, Y_new)
def fit(self, X, Y):
[Y_new, self.old_to_new, self.new_to_old,
num_class] = target_process.translate(Y)
try:
train_accuracy = self.classifier.fit(X, Y_new)
return train_accuracy
except AttributeError as e:
self.classifier = pysol.SOL('stg', num_class, **self.params)
train_accuracy = self.classifier.fit(X, Y_new)
return train_accuracy
def fit(self, X, Y):
num_class = len(set(Y))
try:
return self.classifier.fit(X, Y)
except AttributeError as e:
self.classifier = pysol.SOL('ogd', num_class, **self.params)
accuracy, update, data, iter, err, time = self.classifier.fit(X, Y)
plt.figure
plt.plot(data, err, "r*")
plt.plot(data, err, label="test", color="red", linewidth=2)
plt.xlabel("data")
plt.ylabel("error")
plt.legend()
plt.show()
return accuracy
def fit(self, X, Y):
[Y_new, self.old_to_new, self.new_to_old,
num_class] = target_process.translate(Y)
try:
train_accuracy, update, data, iter, err, time = self.classifier.fit(
X, Y_new)
self.drawFit(data, err, "data", "error", data, update, "data",
"update", data, time, "data", "time", "Ogd")
return train_accuracy
except AttributeError as e:
self.classifier = pysol.SOL('ogd', num_class, **self.params)
train_accuracy, update, data, iter, err, time = self.classifier.fit(
X, Y_new)
self.drawFit(data, err, "data", "error", data, update, "data",
"update", data, time, "data", "time", "Ogd")
return train_accuracy
import pysol
