def test_distributions_gaussian_kernel_random_sample(): d = GaussianKernelDensity([0, 4, 3, 5, 7, 4, 2]) x = numpy.array([5.367586, 2.574708, 2.114238, 2.170925, 4.596907]) assert_array_almost_equal(d.sample(5, random_state=5), x) assert_raises(AssertionError, assert_array_almost_equal, d.sample(5), x)
def test_distributions_gaussian_kernel_random_sample(): d = GaussianKernelDensity([0, 4, 3, 5, 7, 4, 2]) x = numpy.array([5.367586, 2.574708, 2.114238, 2.170925, 4.596907]) assert_array_almost_equal(d.sample(5, random_state=5), x) assert_raises(AssertionError, assert_array_almost_equal, d.sample(5), x)
def plot_histogram(df, feature_name):
d = GaussianKernelDensity(df[feature_name], bandwidth=2)
d.plot(
facecolor="c",
edgecolor="w",
bins=50,
alpha=0.3,
label="Gaussian Kernel Density",
)
def test_gaussian_kernel():
d = GaussianKernelDensity([0, 4, 3, 5, 7, 4, 2])
assert_equal(round(d.log_probability(3.3), 4), -1.7042)
d.fit([1, 6, 8, 3, 2, 4, 7, 2])
assert_equal(round(d.log_probability(1.2), 4), -2.0237)
d.fit([1, 0, 108], weights=[2., 3., 278.])
assert_equal(round(d.log_probability(110), 4), -2.9368)
assert_equal(round(d.log_probability(0), 4), -5.1262)
d.summarize([1, 6, 8, 3])
d.summarize([2, 4, 7])
d.summarize([2])
d.from_summaries()
assert_equal(round(d.log_probability(1.2), 4), -2.0237)
d.summarize([1, 0, 108], weights=[2., 3., 278.])
d.from_summaries()
assert_equal(round(d.log_probability(110), 4), -2.9368)
assert_equal(round(d.log_probability(0), 4), -5.1262)
d.freeze()
d.fit([1, 3, 5, 4, 6, 7, 3, 4, 2])
assert_equal(round(d.log_probability(110), 4), -2.9368)
assert_equal(round(d.log_probability(0), 4), -5.1262)
e = Distribution.from_json(d.to_json())
assert_equal(e.name, "GaussianKernelDensity")
assert_equal(round(e.log_probability(110), 4), -2.9368)
assert_equal(round(e.log_probability(0), 4), -5.1262)
f = pickle.loads(pickle.dumps(e))
assert_equal(f.name, "GaussianKernelDensity")
assert_equal(round(f.log_probability(110), 4), -2.9368)
assert_equal(round(f.log_probability(0), 4), -5.1262)
axes.legend(loc="best")
fig.tight_layout()
fig.show()
fig.savefig("AE_result_.png", dpi=300)
from pomegranate import NaiveBayes, GaussianKernelDensity
data = np.array(list(mse_const_test) + list(mse_vars))
data = np.log(data)
data = data.reshape(-1, 1)
weights = np.ones(len(data))
weights[-len(mse_vars):] = len(mse_const_test) / float(len(mse_vars))
y = np.zeros(len(data))
y[-len(mse_vars):] = np.ones(len(mse_vars))
clf = NaiveBayes([
GaussianKernelDensity(bandwidth=0.1),
GaussianKernelDensity(bandwidth=0.1)
])
clf.fit(data, y, weights=weights)
pred = clf.predict_proba(data)
x = np.array([np.arange(-7, -2, .01)]).T
yy = clf.predict_proba(x)
thresh = 0.5
plt.figure(figsize=(10, 5))
plt.hist(data[pred[:, 0] > thresh],
color='blue',
bins=30,
alpha=0.5,
normed=True,
label="Constant unseen")
plt.hist(data[pred[:, 1] > thresh],
def test_gaussian_kernel(): d = GaussianKernelDensity([0, 4, 3, 5, 7, 4, 2]) assert_equal(round(d.log_probability(3.3), 4), -1.7042) d.fit([1, 6, 8, 3, 2, 4, 7, 2]) assert_equal(round(d.log_probability(1.2), 4), -2.0237) d.fit([1, 0, 108], weights=[2., 3., 278.]) assert_equal(round(d.log_probability(110), 4), -2.9368) assert_equal(round(d.log_probability(0), 4), -5.1262) d.summarize([1, 6, 8, 3]) d.summarize([2, 4, 7]) d.summarize([2]) d.from_summaries() assert_equal(round(d.log_probability(1.2), 4), -2.0237) d.summarize([1, 0, 108], weights=[2., 3., 278.]) d.from_summaries() assert_equal(round(d.log_probability(110), 4), -2.9368) assert_equal(round(d.log_probability(0), 4), -5.1262) d.freeze() d.fit([1, 3, 5, 4, 6, 7, 3, 4, 2]) assert_equal(round(d.log_probability(110), 4), -2.9368) assert_equal(round(d.log_probability(0), 4), -5.1262) e = Distribution.from_json(d.to_json()) assert_equal(e.name, "GaussianKernelDensity") assert_equal(round(e.log_probability(110), 4), -2.9368) assert_equal(round(e.log_probability(0), 4), -5.1262) f = pickle.loads(pickle.dumps(e)) assert_equal(f.name, "GaussianKernelDensity") assert_equal(round(f.log_probability(110), 4), -2.9368) assert_equal(round(f.log_probability(0), 4), -5.1262)