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Merge pull request #57 from PythonPredictions/auc-sorting
sort by AUC selection + typos
2 parents b60a013 + 17c8c60 commit 12de11c

2 files changed

Lines changed: 8 additions & 7 deletions

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.gitignore

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#Ignoired directories in root folder
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#Ignored directories in root folder
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# Byte-compiled / optimized / DLL files
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# Other ignore files
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*.pptx
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*.ppt
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.idea/

cobra/evaluation/plotting_utils.py

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@@ -14,17 +14,17 @@ def plot_univariate_predictor_quality(df_auc: pd.DataFrame,
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Parameters
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----------
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df_auc : pd.DatFrame
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Contains for each variable the train auc and selection auc allong with
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Contains for each variable the train auc and selection auc along with
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a boolean indicating whether or not it is selected based on the
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criteria
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dim : tuple, optional
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tuple with width and lentgh of the plot
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tuple with width and length of the plot
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path : str, optional
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path to store the figure
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"""
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df = (df_auc[df_auc["preselection"]]
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.sort_values(by='AUC train', ascending=False))
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.sort_values(by='AUC selection', ascending=False))
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df = pd.melt(df, id_vars=["predictor"],
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value_vars=["AUC train", "AUC selection"],
@@ -60,7 +60,7 @@ def plot_correlation_matrix(df_corr: pd.DataFrame,
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df_corr : pd.DataFrame
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Correlation matrix
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dim : tuple, optional
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tuple with width and lentgh of the plot
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tuple with width and length of the plot
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path : str, optional
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path to store the figure
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"""
@@ -89,7 +89,7 @@ def plot_performance_curves(model_performance: pd.DataFrame,
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contains train-selection-validation performance for each model trained
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in the forward feature selection
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dim : tuple, optional
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tuple with width and lentgh of the plot
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tuple with width and length of the plot
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path : str, optional
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path to store the figure
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"""
@@ -141,7 +141,7 @@ def plot_variable_importance(df_variable_importance: pd.DataFrame,
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title : str, optional
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Title of the plot
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dim : tuple, optional
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tuple with width and lentgh of the plot
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tuple with width and length of the plot
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path : str, optional
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path to store the figure
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"""

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