tests fix

README.md

@@ -69,11 +69,11 @@ Call the `ATOMClassifier` or `ATOMRegressor` class and provide the data you want
 
 ATOM has multiple data cleaning methods to help you prepare the data for modelling:
 
-    atom.impute(strat_num='knn', strat_cat='most_frequent',  max_frac_rows=0.1)  
+    atom.impute(strat_num='knn', strat_cat='most_frequent',  min_frac_rows=0.7)  
     atom.encode(max_onehot=10, frac_to_other=0.05)  
     atom.outliers(max_sigma=4)  
     atom.balance(oversample=0.8, n_neighbors=15)  
-    atom.feature_selection(strategy='univariate', solver='chi2', max_features=0.9)
+    atom.feature_selection(strategy='univariate', solver='chi2', n_features=0.9)
 
 Run the pipeline with different models:
 

docs_sources/api.md

@@ -395,8 +395,8 @@ cleaning steps. ATOM provides four data cleaning methods to handle missing value
 <a name="atom-impute"></a>
 <pre><em>function</em> atom.ATOM.<strong style="color:#008AB8">impute</strong>(strat_num='remove',
                           strat_cat='remove',
-                          max_frac_rows=0.5,
-                          max_frac_cols=0.5,
+                          min_frac_rows=0.5,
+                          min_frac_cols=0.5,
                           missing=None) 
 <div align="right"><a href="https://github.com/tvdboom/ATOM/blob/master/atom/atom.py#L711">[source]</a></div></pre>
 <div style="padding-left:3%" width="100%">

tests/test_impute.py

@@ -47,18 +47,18 @@ def test_strat_num_parameter():
     pytest.raises(ValueError, atom.impute, strat_num='test')
 
 
-def test_max_frac_rows_parameter():
-    ''' Assert that the mac_frac_rows parameter is set correctly '''
+def test_min_frac_rows_parameter():
+    ''' Assert that the min_frac_rows parameter is set correctly '''
 
     atom = ATOMClassifier(X_dim4, y_dim4)
-    pytest.raises(ValueError, atom.impute, max_frac_rows=1.0)
+    pytest.raises(ValueError, atom.impute, min_frac_rows=1.0)
 
 
-def test_max_frac_cols_parameter():
-    ''' Assert that the mac_frac_cols parameter is set correctly '''
+def test_min_frac_cols_parameter():
+    ''' Assert that the min_frac_cols parameter is set correctly '''
 
     atom = ATOMClassifier(X_dim4, y_dim4)
-    pytest.raises(ValueError, atom.impute, max_frac_cols=5.2)
+    pytest.raises(ValueError, atom.impute, min_frac_cols=5.2)
 
 
 def test_missing_string():

tests/test_plots.py

@@ -355,12 +355,12 @@ def test_plot_gains():
     # When invalid model
     pytest.raises(ValueError, atom.plot_gains, models='unknown')
 
-    # When model with no rpedict_proba method
+    # When model with no predict_proba method
     pytest.raises(ValueError, atom.pa.plot_gains)
 
     # When correct
     atom.tree.plot_gains(display=False)
-    atom.plot_gains(display=False)
+    atom.plot_gains(['tree', 'lgb'], display=False)
     assert 1 == 1
 
 
@@ -383,5 +383,5 @@ def test_plot_lift():
 
     # When correct
     atom.tree.plot_lift(display=False)
-    atom.plot_lift(display=False)
+    atom.plot_lift(['tree', 'lgb'], display=False)
     assert 1 == 1