Python sklearn.feature_selection() Examples

The following are 5 code examples of sklearn.feature_selection(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module sklearn , or try the search function .
Example #1
Source File: DataAnalysis.py    From Predicting-Health-Insurance-Cost with BSD 3-Clause "New" or "Revised" License 8 votes vote down vote up 
def featuresFromFeatureSelection(X,Y,columnNames):
    
    for f in columnNames:
        print(f)
    X_new_withfitTransform = SelectKBest(chi2, k=34).fit(X, Y)
    colors = getColorNames()
    counter  = 0
    
    scores = X_new_withfitTransform.scores_
    scores_scaled = np.divide(scores, 1000) 
        
    for score in scores_scaled:
        #if(score > 10):
        #print('Feature {:>34}'.format(columnNames[counter]))
        print('{:>34}  '.format( score))
        '''Plot a graph'''    
        plt.bar(counter, score,color=colors[counter])
        counter +=1 

    plt.ylabel('Scores(1k)')
    plt.title('Scores calculated by Chi-Square Test')
    plt.legend(columnNames, bbox_to_anchor=(0., 0.8, 1., .102), loc=3,ncol=5, mode="expand", borderaxespad=0.)
    plt.show()
    
    #print(feature_selection.chi2(X,Y))
Example #2
Source File: test_base.py    From Mastering-Elasticsearch-7.0 with MIT License 6 votes vote down vote up 
def test_clone():
    # Tests that clone creates a correct deep copy.
    # We create an estimator, make a copy of its original state
    # (which, in this case, is the current state of the estimator),
    # and check that the obtained copy is a correct deep copy.

    from sklearn.feature_selection import SelectFpr, f_classif

    selector = SelectFpr(f_classif, alpha=0.1)
    new_selector = clone(selector)
    assert selector is not new_selector
    assert_equal(selector.get_params(), new_selector.get_params())

    selector = SelectFpr(f_classif, alpha=np.zeros((10, 2)))
    new_selector = clone(selector)
    assert selector is not new_selector
Example #3
Source File: test_base.py    From twitter-stock-recommendation with MIT License 6 votes vote down vote up 
def test_clone():
    # Tests that clone creates a correct deep copy.
    # We create an estimator, make a copy of its original state
    # (which, in this case, is the current state of the estimator),
    # and check that the obtained copy is a correct deep copy.

    from sklearn.feature_selection import SelectFpr, f_classif

    selector = SelectFpr(f_classif, alpha=0.1)
    new_selector = clone(selector)
    assert_true(selector is not new_selector)
    assert_equal(selector.get_params(), new_selector.get_params())

    selector = SelectFpr(f_classif, alpha=np.zeros((10, 2)))
    new_selector = clone(selector)
    assert_true(selector is not new_selector)
Example #4
Source File: test_base.py    From Mastering-Elasticsearch-7.0 with MIT License 5 votes vote down vote up 
def test_clone_2():
    # Tests that clone doesn't copy everything.
    # We first create an estimator, give it an own attribute, and
    # make a copy of its original state. Then we check that the copy doesn't
    # have the specific attribute we manually added to the initial estimator.

    from sklearn.feature_selection import SelectFpr, f_classif

    selector = SelectFpr(f_classif, alpha=0.1)
    selector.own_attribute = "test"
    new_selector = clone(selector)
    assert not hasattr(new_selector, "own_attribute")
Example #5
Source File: test_base.py    From twitter-stock-recommendation with MIT License 5 votes vote down vote up 
def test_clone_2():
    # Tests that clone doesn't copy everything.
    # We first create an estimator, give it an own attribute, and
    # make a copy of its original state. Then we check that the copy doesn't
    # have the specific attribute we manually added to the initial estimator.

    from sklearn.feature_selection import SelectFpr, f_classif

    selector = SelectFpr(f_classif, alpha=0.1)
    selector.own_attribute = "test"
    new_selector = clone(selector)
    assert_false(hasattr(new_selector, "own_attribute"))