def judge(self, X, y):
predictions = [int(i) for i in self.predict(X)]
title = "Clustering of Kepler stars with {} mixtures".format(self._K)
labels = ["Class: {}".format(i) for i in range(0, self._K)]
plot_classification(y[1],
y[0],
predictions,
class_labels=labels,
title=title)
def judge(self, X, y):
plot_classification(y[1],
y[0], [int(i) for i in self.predict(X)],
class_labels=['Red giant branch', 'Red clumps'],
title="Gaussian Naive Bayes classification")
def judge(self, X, y):
plot_classification(y[1],
y[0],
[1 if i >= 0.5 else 0 for i in self.predict(X)],
class_labels=['Red giant branch', 'Red clumps'],
title="Baseline Neural Network classification")
def judge(self, X, y): plot_classification(y[1], y[0], [int(i) for i in self.predict(X)], class_labels=['Red giant branch', 'Red clumps'], title="Logistic Regression classification")
def judge(self, X, y):
plot_classification(y[1],
y[0], [int(i) for i in self.predict(X)],
class_labels=['Red giant branch', 'Red clumps'],
title="K-Nearest Neighbors classification")