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sort by AUC selection + typos #57

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Merged
sandervh14 merged 2 commits into from
Mar 31, 2021
Merged

sort by AUC selection + typos #57

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74af6f1
sort by AUC selection + typos
sborms Mar 31, 2021
17c8c60
remove .idea + add to .gitignore
sborms Mar 31, 2021
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3 changes: 2 additions & 1 deletion .gitignore
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Original file line number Diff line number Diff line change
@@ -1,4 +1,4 @@
#Ignoired directories in root folder
#Ignored directories in root folder


# Byte-compiled / optimized / DLL files
Expand Down Expand Up @@ -109,3 +109,4 @@ ENV/
# Other ignore files
*.pptx
*.ppt
.idea/
12 changes: 6 additions & 6 deletions cobra/evaluation/plotting_utils.py
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Expand Up @@ -14,17 +14,17 @@ def plot_univariate_predictor_quality(df_auc: pd.DataFrame,
Parameters
----------
df_auc : pd.DatFrame
Contains for each variable the train auc and selection auc allong with
Contains for each variable the train auc and selection auc along with
a boolean indicating whether or not it is selected based on the
criteria
dim : tuple, optional
tuple with width and lentgh of the plot
tuple with width and length of the plot
path : str, optional
path to store the figure
"""

df = (df_auc[df_auc["preselection"]]
.sort_values(by='AUC train', ascending=False))
.sort_values(by='AUC selection', ascending=False))

df = pd.melt(df, id_vars=["predictor"],
value_vars=["AUC train", "AUC selection"],
Expand Down Expand Up @@ -60,7 +60,7 @@ def plot_correlation_matrix(df_corr: pd.DataFrame,
df_corr : pd.DataFrame
Correlation matrix
dim : tuple, optional
tuple with width and lentgh of the plot
tuple with width and length of the plot
path : str, optional
path to store the figure
"""
Expand Down Expand Up @@ -89,7 +89,7 @@ def plot_performance_curves(model_performance: pd.DataFrame,
contains train-selection-validation performance for each model trained
in the forward feature selection
dim : tuple, optional
tuple with width and lentgh of the plot
tuple with width and length of the plot
path : str, optional
path to store the figure
"""
Expand Down Expand Up @@ -141,7 +141,7 @@ def plot_variable_importance(df_variable_importance: pd.DataFrame,
title : str, optional
Title of the plot
dim : tuple, optional
tuple with width and lentgh of the plot
tuple with width and length of the plot
path : str, optional
path to store the figure
"""
Expand Down