openGPMP
Open Source Mathematics Package
Public Member Functions | Properties | Static Private Attributes | List of all members
pygpmp.ml.ml.LinearRegression Class Reference
Inheritance diagram for pygpmp.ml.ml.LinearRegression:

Public Member Functions

def __init__ (self)
 
def calculate_coeffecient (self)
 
def calculate_constant (self)
 
def data_size (self)
 
def return_coeffecient (self)
 
def return_constant (self)
 
def best_fit (self)
 
def get_input (self, *args)
 
def split_data (self, test_size, seed, shuffle)
 
def show_data (self)
 
def predict (self, *args)
 
def error_in (self, *args)
 
def error_square (self)
 
def mse (self, x_data, y_data)
 
def r_sqrd (self, x_data, y_data)
 
def num_rows (self, input)
 

Properties

 thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
 
 x = property(_ml.LinearRegression_x_get, _ml.LinearRegression_x_set)
 
 y = property(_ml.LinearRegression_y_get, _ml.LinearRegression_y_set)
 
 coeff = property(_ml.LinearRegression_coeff_get, _ml.LinearRegression_coeff_set)
 
 constant = property(_ml.LinearRegression_constant_get, _ml.LinearRegression_constant_set)
 
 sum_xy = property(_ml.LinearRegression_sum_xy_get, _ml.LinearRegression_sum_xy_set)
 
 sum_x = property(_ml.LinearRegression_sum_x_get, _ml.LinearRegression_sum_x_set)
 
 sum_y = property(_ml.LinearRegression_sum_y_get, _ml.LinearRegression_sum_y_set)
 
 sum_x_square = property(_ml.LinearRegression_sum_x_square_get, _ml.LinearRegression_sum_x_square_set)
 
 sum_y_square = property(_ml.LinearRegression_sum_y_square_get, _ml.LinearRegression_sum_y_square_set)
 
 x_train = property(_ml.LinearRegression_x_train_get, _ml.LinearRegression_x_train_set)
 
 y_train = property(_ml.LinearRegression_y_train_get, _ml.LinearRegression_y_train_set)
 
 x_test = property(_ml.LinearRegression_x_test_get, _ml.LinearRegression_x_test_set)
 
 y_test = property(_ml.LinearRegression_y_test_get, _ml.LinearRegression_y_test_set)
 

Static Private Attributes

 __repr__ = _swig_repr
 
 __swig_destroy__ = _ml.delete_LinearRegression
 

Detailed Description

Definition at line 121 of file ml.py.

Constructor & Destructor Documentation

◆ __init__()

def pygpmp.ml.ml.LinearRegression.__init__ (   self)

Definition at line 138 of file ml.py.

138  def __init__(self):
139  _ml.LinearRegression_swiginit(self, _ml.new_LinearRegression())
140 

Member Function Documentation

◆ best_fit()

def pygpmp.ml.ml.LinearRegression.best_fit (   self)

Definition at line 156 of file ml.py.

156  def best_fit(self):
157  return _ml.LinearRegression_best_fit(self)
158 

◆ calculate_coeffecient()

def pygpmp.ml.ml.LinearRegression.calculate_coeffecient (   self)

Definition at line 141 of file ml.py.

141  def calculate_coeffecient(self):
142  return _ml.LinearRegression_calculate_coeffecient(self)
143 

◆ calculate_constant()

def pygpmp.ml.ml.LinearRegression.calculate_constant (   self)

Definition at line 144 of file ml.py.

144  def calculate_constant(self):
145  return _ml.LinearRegression_calculate_constant(self)
146 

◆ data_size()

def pygpmp.ml.ml.LinearRegression.data_size (   self)

Definition at line 147 of file ml.py.

147  def data_size(self):
148  return _ml.LinearRegression_data_size(self)
149 

◆ error_in()

def pygpmp.ml.ml.LinearRegression.error_in (   self,
*  args 
)

Definition at line 171 of file ml.py.

171  def error_in(self, *args):
172  return _ml.LinearRegression_error_in(self, *args)
173 

◆ error_square()

def pygpmp.ml.ml.LinearRegression.error_square (   self)

Definition at line 174 of file ml.py.

174  def error_square(self):
175  return _ml.LinearRegression_error_square(self)
176 

◆ get_input()

def pygpmp.ml.ml.LinearRegression.get_input (   self,
*  args 
)

Definition at line 159 of file ml.py.

159  def get_input(self, *args):
160  return _ml.LinearRegression_get_input(self, *args)
161 

◆ mse()

def pygpmp.ml.ml.LinearRegression.mse (   self,
  x_data,
  y_data 
)

Definition at line 177 of file ml.py.

177  def mse(self, x_data, y_data):
178  return _ml.LinearRegression_mse(self, x_data, y_data)
179 

◆ num_rows()

def pygpmp.ml.ml.LinearRegression.num_rows (   self,
  input 
)

Definition at line 183 of file ml.py.

183  def num_rows(self, input):
184  return _ml.LinearRegression_num_rows(self, input)

◆ predict()

def pygpmp.ml.ml.LinearRegression.predict (   self,
*  args 
)

Definition at line 168 of file ml.py.

168  def predict(self, *args):
169  return _ml.LinearRegression_predict(self, *args)
170 

◆ r_sqrd()

def pygpmp.ml.ml.LinearRegression.r_sqrd (   self,
  x_data,
  y_data 
)

Definition at line 180 of file ml.py.

180  def r_sqrd(self, x_data, y_data):
181  return _ml.LinearRegression_r_sqrd(self, x_data, y_data)
182 

◆ return_coeffecient()

def pygpmp.ml.ml.LinearRegression.return_coeffecient (   self)

Definition at line 150 of file ml.py.

150  def return_coeffecient(self):
151  return _ml.LinearRegression_return_coeffecient(self)
152 

◆ return_constant()

def pygpmp.ml.ml.LinearRegression.return_constant (   self)

Definition at line 153 of file ml.py.

153  def return_constant(self):
154  return _ml.LinearRegression_return_constant(self)
155 

◆ show_data()

def pygpmp.ml.ml.LinearRegression.show_data (   self)

Definition at line 165 of file ml.py.

165  def show_data(self):
166  return _ml.LinearRegression_show_data(self)
167 

◆ split_data()

def pygpmp.ml.ml.LinearRegression.split_data (   self,
  test_size,
  seed,
  shuffle 
)

Definition at line 162 of file ml.py.

162  def split_data(self, test_size, seed, shuffle):
163  return _ml.LinearRegression_split_data(self, test_size, seed, shuffle)
164 

Member Data Documentation

◆ __repr__

pygpmp.ml.ml.LinearRegression.__repr__ = _swig_repr
staticprivate

Definition at line 123 of file ml.py.

◆ __swig_destroy__

pygpmp.ml.ml.LinearRegression.__swig_destroy__ = _ml.delete_LinearRegression
staticprivate

Definition at line 185 of file ml.py.

Property Documentation

◆ coeff

pygpmp.ml.ml.LinearRegression.coeff = property(_ml.LinearRegression_coeff_get, _ml.LinearRegression_coeff_set)
static

Definition at line 126 of file ml.py.

◆ constant

pygpmp.ml.ml.LinearRegression.constant = property(_ml.LinearRegression_constant_get, _ml.LinearRegression_constant_set)
static

Definition at line 127 of file ml.py.

◆ sum_x

pygpmp.ml.ml.LinearRegression.sum_x = property(_ml.LinearRegression_sum_x_get, _ml.LinearRegression_sum_x_set)
static

Definition at line 129 of file ml.py.

◆ sum_x_square

pygpmp.ml.ml.LinearRegression.sum_x_square = property(_ml.LinearRegression_sum_x_square_get, _ml.LinearRegression_sum_x_square_set)
static

Definition at line 131 of file ml.py.

◆ sum_xy

pygpmp.ml.ml.LinearRegression.sum_xy = property(_ml.LinearRegression_sum_xy_get, _ml.LinearRegression_sum_xy_set)
static

Definition at line 128 of file ml.py.

◆ sum_y

pygpmp.ml.ml.LinearRegression.sum_y = property(_ml.LinearRegression_sum_y_get, _ml.LinearRegression_sum_y_set)
static

Definition at line 130 of file ml.py.

◆ sum_y_square

pygpmp.ml.ml.LinearRegression.sum_y_square = property(_ml.LinearRegression_sum_y_square_get, _ml.LinearRegression_sum_y_square_set)
static

Definition at line 132 of file ml.py.

◆ thisown

pygpmp.ml.ml.LinearRegression.thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag")
static

Definition at line 122 of file ml.py.

◆ x

pygpmp.ml.ml.LinearRegression.x = property(_ml.LinearRegression_x_get, _ml.LinearRegression_x_set)
static

Definition at line 124 of file ml.py.

◆ x_test

pygpmp.ml.ml.LinearRegression.x_test = property(_ml.LinearRegression_x_test_get, _ml.LinearRegression_x_test_set)
static

Definition at line 135 of file ml.py.

◆ x_train

pygpmp.ml.ml.LinearRegression.x_train = property(_ml.LinearRegression_x_train_get, _ml.LinearRegression_x_train_set)
static

Definition at line 133 of file ml.py.

◆ y

pygpmp.ml.ml.LinearRegression.y = property(_ml.LinearRegression_y_get, _ml.LinearRegression_y_set)
static

Definition at line 125 of file ml.py.

◆ y_test

pygpmp.ml.ml.LinearRegression.y_test = property(_ml.LinearRegression_y_test_get, _ml.LinearRegression_y_test_set)
static

Definition at line 136 of file ml.py.

◆ y_train

pygpmp.ml.ml.LinearRegression.y_train = property(_ml.LinearRegression_y_train_get, _ml.LinearRegression_y_train_set)
static

Definition at line 134 of file ml.py.

The documentation for this class was generated from the following file:
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