Xiao Wei xiaowei1234

Statistics and modeling in Python and a little R

xiaowei1234 / Expression_isnull.py

Created July 27, 2019 00:57

create binary column on null values

	wrap1 = DataFrameMapper([
	('col_with_nulls', ExpressionTransformer("0 if pandas.isnull(X[0]) else 1")
	])

xiaowei1234 / GLM vs OLS Lasso penalty.py

Created March 4, 2022 17:02

A comparison of GLM vs OLS lasso penalty regression

	import numpy as np
	from sklearn.linear_model import PoissonRegressor, Lasso

	X_array = np.asarray([[1, 2], [1, 3], [1, 4], [1, 3]])
	y = np.asarray([2, 2, 3, 2])
	Preg_alpha_1 = PoissonRegressor(alpha=1., fit_intercept=False).fit(X_array, y)
	print('alpha 1', Preg_alpha_1.coef_)
	Preg_alpha_2 = PoissonRegressor(alpha=2., fit_intercept=False).fit(X_array/2., y)
	print('alpha 2', Preg_alpha_2.coef_)
	Lreg_alpha_1 = Lasso(alpha=1., fit_intercept=False).fit(X_array, y)

xiaowei1234 / glm vs lasso v2.py

Last active March 4, 2022 19:08

	import numpy as np
	from sklearn.linear_model import PoissonRegressor, Lasso, Ridge
	import statsmodels.api as sm

	X_array = np.asarray([[1, 2], [1, 3], [1, 4], [1, 3]])
	y = np.asarray([2, 2, 3, 2])
	Preg_alpha_1 = PoissonRegressor(alpha=1., fit_intercept=False).fit(X_array, y)
	print('alpha 1 Poisson Reg', Preg_alpha_1.coef_)
	Preg_alpha_2 = PoissonRegressor(alpha=2., fit_intercept=False).fit(X_array*4., y)
	print('alpha 2 Poisson Reg', Preg_alpha_2.coef_)