models.py
def predict(self, x):
    '''
    Computes a 0-1 matrix of predicted labels for each instance.
    
    Params:
      x - input features
    
    Returns:
      A 0-1 matrix of predicted labels.
    '''
    dv = self.decision_function(x)
    return repredict(dv, self.t1, self.t2)

    Computes a 0-1 matrix of predicted labels for each instance.
    
    Params:
      x - input features
    
    Returns:
      A 0-1 matrix of predicted labels.
    
Computes a 0-1 matrix of predicted labels for each instance.
Params:
x - input features

A 0-1 matrix of predicted labels.
Computes a 0 - 1 matrix of predicted labels for each instance . Params : x - input features A 0 - 1 matrix of predicted labels .
def predict(self, x):
    dv = self.decision_function(x)
    return repredict(dv, self.t1, self.t2)
def predict ( self , x ) : dv = self . decision_function ( x ) return repredict ( dv , self . t1 , self . t2 )
Computes a 0-1 matrix of predicted labels for each instance.
Computes a 0 - 1 matrix of predicted labels for each instance .
'''
    Computes a 0-1 matrix of predicted labels for each instance.
    
    Params:
      x - input features
    
    Returns:
      A 0-1 matrix of predicted labels.
    '''
self
x