__init__(self) | pygpmp.ml.ml.LinearRegression | |
__repr__ | pygpmp.ml.ml.LinearRegression | privatestatic |
__swig_destroy__ | pygpmp.ml.ml.LinearRegression | privatestatic |
best_fit(self) | pygpmp.ml.ml.LinearRegression | |
calculate_coeffecient(self) | pygpmp.ml.ml.LinearRegression | |
calculate_constant(self) | pygpmp.ml.ml.LinearRegression | |
coeff | pygpmp.ml.ml.LinearRegression | static |
constant | pygpmp.ml.ml.LinearRegression | static |
data_size(self) | pygpmp.ml.ml.LinearRegression | |
error_in(self, *args) | pygpmp.ml.ml.LinearRegression | |
error_square(self) | pygpmp.ml.ml.LinearRegression | |
get_input(self, *args) | pygpmp.ml.ml.LinearRegression | |
mse(self, x_data, y_data) | pygpmp.ml.ml.LinearRegression | |
num_rows(self, input) | pygpmp.ml.ml.LinearRegression | |
predict(self, *args) | pygpmp.ml.ml.LinearRegression | |
r_sqrd(self, x_data, y_data) | pygpmp.ml.ml.LinearRegression | |
return_coeffecient(self) | pygpmp.ml.ml.LinearRegression | |
return_constant(self) | pygpmp.ml.ml.LinearRegression | |
show_data(self) | pygpmp.ml.ml.LinearRegression | |
split_data(self, test_size, seed, shuffle) | pygpmp.ml.ml.LinearRegression | |
sum_x | pygpmp.ml.ml.LinearRegression | static |
sum_x_square | pygpmp.ml.ml.LinearRegression | static |
sum_xy | pygpmp.ml.ml.LinearRegression | static |
sum_y | pygpmp.ml.ml.LinearRegression | static |
sum_y_square | pygpmp.ml.ml.LinearRegression | static |
thisown | pygpmp.ml.ml.LinearRegression | static |
x | pygpmp.ml.ml.LinearRegression | static |
x_test | pygpmp.ml.ml.LinearRegression | static |
x_train | pygpmp.ml.ml.LinearRegression | static |
y | pygpmp.ml.ml.LinearRegression | static |
y_test | pygpmp.ml.ml.LinearRegression | static |
y_train | pygpmp.ml.ml.LinearRegression | static |