b104ef8ea5f6e98b0b05a5cf068bba0c8689d445,rankeval/visualization/effectiveness.py,,plot_tree_wise_average_contribution,#Any#,462
Before Change
k_values = performance.sel(dataset=dataset, model=model)
a = axes.plot(k_values.values)
axes.set_title(performance.name + " for " + dataset.name)
axes.set_xlabel("Number of trees")
axes.legend(performance.coords["model"].values)
plt.tight_layout()
After Change
sharex=True, squeeze=False)
fig.suptitle(performance.name + " for " + dataset.name)
for i, model in enumerate(performance.coords["model"].values):
k_values = performance.sel(dataset=dataset, model=model)
axes[i, 0].plot(k_values.values)
axes[i, 0].legend((model,), loc="upper center")
axes[i, 0].set_xlabel("Number of trees")
fig_list.append(fig)
In pattern: SUPERPATTERN
Frequency: 3
Non-data size: 3
Instances
Project Name: hpclab/rankeval
Commit Name: b104ef8ea5f6e98b0b05a5cf068bba0c8689d445
Time: 2017-07-27
Author: cristina.i.muntean@gmail.com
File Name: rankeval/visualization/effectiveness.py
Class Name:
Method Name: plot_tree_wise_average_contribution
Project Name: milesial/Pytorch-UNet
Commit Name: ff1ac0936c118d129bc8a8014958948d3b3883be
Time: 2019-10-26
Author: milesial@users.noreply.github.com
File Name: utils/data_vis.py
Class Name:
Method Name: plot_img_and_mask
Project Name: scikit-learn-contrib/imbalanced-learn
Commit Name: 153f6e0ff5729fc22b68d5f6e0fd05edf96d8c2c
Time: 2019-11-17
Author: g.lemaitre58@gmail.com
File Name: examples/datasets/plot_make_imbalance.py
Class Name:
Method Name: