featureselection.py
def reliefF(X, y, n_features):
    '''
    Runs ReliefF algorithm on the data (X) and the target values (y) and finds 
    the index of the top n_features number of features.

    Args:
        X: A Numpy array containing the dataset
        y: A Numpy array consisting of the target values
        n_features: An integer specifying how many features should be selected

    Returns a list containing the indices of the features that have been selected
    '''
    fs = ReliefF(n_neighbors=100, n_features_to_keep=n_features)
    fs.fit_transform(X, y)
    index = fs.top_features[:n_features]
    return index

    Runs ReliefF algorithm on the data (X) and the target values (y) and finds 
    the index of the top n_features number of features.

    Args:
        X: A Numpy array containing the dataset
        y: A Numpy array consisting of the target values
        n_features: An integer specifying how many features should be selected

    Returns a list containing the indices of the features that have been selected
    
Runs ReliefF algorithm on the data (X) and the target values (y) and finds
the index of the top n_features number of features.
Runs ReliefF algorithm on the data ( X ) and the target values ( y ) and finds the index of the top n_features number of features .
def reliefF(X, y, n_features):
    fs = ReliefF(n_neighbors=100, n_features_to_keep=n_features)
    fs.fit_transform(X, y)
    index = fs.top_features[:n_features]
    return index
def reliefF ( X , y , n_features ) : fs = ReliefF ( n_neighbors = 100 , n_features_to_keep = n_features ) fs . fit_transform ( X , y ) index = fs . top_features [ : n_features ] return index
Runs ReliefF algorithm on the data (X) and the target values (y) and finds
the index of the top n_features number of features.
Runs ReliefF algorithm on the data ( X ) and the target values ( y ) and finds the index of the top n_features number of features .
'''
    Runs ReliefF algorithm on the data (X) and the target values (y) and finds 
    the index of the top n_features number of features.

    Args:
        X: A Numpy array containing the dataset
        y: A Numpy array consisting of the target values
        n_features: An integer specifying how many features should be selected

    Returns a list containing the indices of the features that have been selected
    '''
X
A Numpy array containing the dataset
A Numpy array containing the dataset
y
A Numpy array consisting of the target values
A Numpy array consisting of the target values
n_features
An integer specifying how many features should be selected
An integer specifying how many features should be selected