def hsic(num_features, hsic_data, method='regression'):
hsic_lasso = HSICLasso()
hsic_lasso.input(hsic_data)
if method == 'regression':
hsic_lasso.regression(num_features)
else:
hsic_lasso.classification(num_features)
return hsic_lasso.get_features()
def hsic_sel(csv, no_features, method='classification'):
hsic_lasso = HSICLasso()
hsic_lasso.input(csv)
if method == 'regression':
hsic_lasso.regression(no_features)
else:
hsic_lasso.classification(no_features)
return hsic_lasso.get_features()
def main():
hsic_lasso = HSICLasso()
#out_list = ['c'+str(i) for i in range(1,51)]
#print (out_list)
hsic_lasso.input("./user_data_new.csv",
output_list=[
'c1', 'c2', 'c3', 'c4', 'c5,', 'c6', 'c7', 'c8', 'c9',
'c10'
])
# ,'c11', 'c12', 'c13', 'c14', 'c15,', 'c16', 'c17', 'c18', 'c19', 'c20','c21', 'c22', 'c23', 'c24', 'c25,', 'c26', 'c27', 'c28', 'c29', 'c30'])
hsic_lasso.regression(100, B=50)
hsic_lasso.dump()
select_index = hsic_lasso.get_index()
print(select_index)
print(hsic_lasso.get_index_score())
#hsic_lasso.plot_path()
print(hsic_lasso.get_features())
X_select = hsic_lasso.X_in[select_index, :]
np.savetxt('X_select.txt', X_select, fmt=str('%.5f'), encoding='utf-8')
def HSICLasso(self):
df_ = self.data.copy()
cols = list(df_.columns)[:-1] + ['class']
df_.columns = cols
hsic_lasso = HSICLasso()
hsic_lasso.input(self.X_train.values, self.Y_train.values)
if self.type == CLASSIFICATION:
hsic_lasso.classification(self.num_top_features)
elif self.type == REGRESSION:
hsic_lasso.regression(self.num_top_features)
feats = [
df_.columns[int(val) - 1] for val in hsic_lasso.get_features()
]
for feat, imp in zip(feats, hsic_lasso.get_index_score()):
features_[feat] = imp
self.report_feature_importance(features_,
self.num_top_features,
label="HSICLasso")
from pyHSICLasso import HSICLasso
hsic_lasso = HSICLasso()
hsic_lasso.input("SNR-26415.csv")
print(hsic_lasso.classification(100))
hsic_lasso.get_features()
l = []
l.append(hsic_lasso.get_features())
print(hsic_lasso.get_features())
print(len(l))
temp = 0
hsic_lasso.dump()
for i in range(0, len(l)):
print(l[i])
temp = temp + 1
print(temp)
