ModelEvaluatorPlot.scores

static ModelEvaluatorPlot.scores(df_eval, figsize=(6, 4), colors=None, metrics=None)[source]

Plot cross-validated scores per (model, metric) as grouped bars with CI error bars.

One bar group per metric holds one bar per model; the error bars show the bootstrap confidence interval of the mean (falling back to the fold std where the CI is NaN), so models are compared at a glance with their uncertainty.

Added in version 1.1.0.

Parameters:

df_eval (pd.DataFrame, shape (n_models * n_metrics, 7)) – Evaluation table from ModelEvaluator.run() with columns model, metric, score, score_std, ci_low, ci_high, and n_scores. Error bars use the bootstrap CI (ci_low / ci_high), falling back to score_std where the CI is NaN.
figsize (tuple, default=(6, 4)) – Figure dimensions (width, height) in inches.
colors (list of str, optional) – One color per model (in first-appearance order). Defaults to the package color list.
metrics (list of str, optional) – Subset and order of metrics to show on the x-axis. Defaults to all metrics in df_eval (first-appearance order).

Returns:

fig (Figure) – Figure object for the evaluation plot.
ax (Axes) – Axes object of the grouped bar chart.

See also

ModelEvaluator.run(): the respective computation method.

Examples

ModelEvaluatorPlot.scores draws the cross-validated scores from ModelEvaluator.run as grouped bars with confidence-interval error bars. First, the dataset, feature matrix, and evaluation:

import aaanalysis as aa
aa.options["verbose"] = False  # Disable verbosity

# DOM_GSEC example dataset + a small feature set (see [Breimann25]_)
df_seq = aa.load_dataset(name="DOM_GSEC")
labels = df_seq["label"].to_list()
df_feat = aa.load_features(name="DOM_GSEC").head(20)

# Build the CPP feature matrix X
sf = aa.SequenceFeature()
df_parts = sf.get_df_parts(df_seq=df_seq)
X = sf.feature_matrix(features=df_feat["feature"], df_parts=df_parts)

me = aa.ModelEvaluator(models=["rf", "svm"], random_state=42, verbose=False)
df_eval = me.run(X, labels, n_rounds=3)

/Users/stephanbreimann/Programming/1Packages/aaanalysis/.venv/lib/python3.13/site-packages/sklearn/svm/_base.py:239: FutureWarning: The probability parameter was deprecated in 1.9 and will be removed in version 1.11. Use CalibratedClassifierCV(SVC(), ensemble=False) instead of SVC(probability=True)
  warnings.warn(
/Users/stephanbreimann/Programming/1Packages/aaanalysis/.venv/lib/python3.13/site-packages/sklearn/svm/_base.py:239: FutureWarning: The probability parameter was deprecated in 1.9 and will be removed in version 1.11. Use CalibratedClassifierCV(SVC(), ensemble=False) instead of SVC(probability=True)
  warnings.warn(
/Users/stephanbreimann/Programming/1Packages/aaanalysis/.venv/lib/python3.13/site-packages/sklearn/svm/_base.py:239: FutureWarning: The probability parameter was deprecated in 1.9 and will be removed in version 1.11. Use CalibratedClassifierCV(SVC(), ensemble=False) instead of SVC(probability=True)
  warnings.warn(
/Users/stephanbreimann/Programming/1Packages/aaanalysis/.venv/lib/python3.13/site-packages/sklearn/svm/_base.py:239: FutureWarning: The probability parameter was deprecated in 1.9 and will be removed in version 1.11. Use CalibratedClassifierCV(SVC(), ensemble=False) instead of SVC(probability=True)
  warnings.warn(
/Users/stephanbreimann/Programming/1Packages/aaanalysis/.venv/lib/python3.13/site-packages/sklearn/svm/_base.py:239: FutureWarning: The probability parameter was deprecated in 1.9 and will be removed in version 1.11. Use CalibratedClassifierCV(SVC(), ensemble=False) instead of SVC(probability=True)
  warnings.warn(
/Users/stephanbreimann/Programming/1Packages/aaanalysis/.venv/lib/python3.13/site-packages/sklearn/svm/_base.py:239: FutureWarning: The probability parameter was deprecated in 1.9 and will be removed in version 1.11. Use CalibratedClassifierCV(SVC(), ensemble=False) instead of SVC(probability=True)
  warnings.warn(
/Users/stephanbreimann/Programming/1Packages/aaanalysis/.venv/lib/python3.13/site-packages/sklearn/svm/_base.py:239: FutureWarning: The probability parameter was deprecated in 1.9 and will be removed in version 1.11. Use CalibratedClassifierCV(SVC(), ensemble=False) instead of SVC(probability=True)
  warnings.warn(
/Users/stephanbreimann/Programming/1Packages/aaanalysis/.venv/lib/python3.13/site-packages/sklearn/svm/_base.py:239: FutureWarning: The probability parameter was deprecated in 1.9 and will be removed in version 1.11. Use CalibratedClassifierCV(SVC(), ensemble=False) instead of SVC(probability=True)
  warnings.warn(
/Users/stephanbreimann/Programming/1Packages/aaanalysis/.venv/lib/python3.13/site-packages/sklearn/svm/_base.py:239: FutureWarning: The probability parameter was deprecated in 1.9 and will be removed in version 1.11. Use CalibratedClassifierCV(SVC(), ensemble=False) instead of SVC(probability=True)
  warnings.warn(
/Users/stephanbreimann/Programming/1Packages/aaanalysis/.venv/lib/python3.13/site-packages/sklearn/svm/_base.py:239: FutureWarning: The probability parameter was deprecated in 1.9 and will be removed in version 1.11. Use CalibratedClassifierCV(SVC(), ensemble=False) instead of SVC(probability=True)
  warnings.warn(
/Users/stephanbreimann/Programming/1Packages/aaanalysis/.venv/lib/python3.13/site-packages/sklearn/svm/_base.py:239: FutureWarning: The probability parameter was deprecated in 1.9 and will be removed in version 1.11. Use CalibratedClassifierCV(SVC(), ensemble=False) instead of SVC(probability=True)
  warnings.warn(
/Users/stephanbreimann/Programming/1Packages/aaanalysis/.venv/lib/python3.13/site-packages/sklearn/svm/_base.py:239: FutureWarning: The probability parameter was deprecated in 1.9 and will be removed in version 1.11. Use CalibratedClassifierCV(SVC(), ensemble=False) instead of SVC(probability=True)
  warnings.warn(
/Users/stephanbreimann/Programming/1Packages/aaanalysis/.venv/lib/python3.13/site-packages/sklearn/svm/_base.py:239: FutureWarning: The probability parameter was deprecated in 1.9 and will be removed in version 1.11. Use CalibratedClassifierCV(SVC(), ensemble=False) instead of SVC(probability=True)
  warnings.warn(
/Users/stephanbreimann/Programming/1Packages/aaanalysis/.venv/lib/python3.13/site-packages/sklearn/svm/_base.py:239: FutureWarning: The probability parameter was deprecated in 1.9 and will be removed in version 1.11. Use CalibratedClassifierCV(SVC(), ensemble=False) instead of SVC(probability=True)
  warnings.warn(
/Users/stephanbreimann/Programming/1Packages/aaanalysis/.venv/lib/python3.13/site-packages/sklearn/svm/_base.py:239: FutureWarning: The probability parameter was deprecated in 1.9 and will be removed in version 1.11. Use CalibratedClassifierCV(SVC(), ensemble=False) instead of SVC(probability=True)
  warnings.warn(

Plot df_eval with a figsize, per-model colors, and an explicit metrics order:

import matplotlib.pyplot as plt
aa.plot_settings()
fig, ax = aa.ModelEvaluatorPlot.scores(df_eval=df_eval, figsize=(6, 4),
                                       colors=["tab:blue", "tab:orange"],
                                       metrics=["balanced_accuracy", "mcc"])
plt.tight_layout()
plt.show()

../_images/me_plot_scores_1_output_3_0.png