I'm using sns.factorplot to visualize the features importances ranking. Nine features was selected and they need to be ranked by how many iterations through before they were elimited by SVM-RFE
.
meanplot = pd.DataFrame(list(r.items()), columns=['Features','Ranking'])
meanplot = meanplot.sort_values('Ranking', ascending=False)
sns.factorplot(x="Ranking", y="Features", data = meanplot[:9], kind="bar", size=4, aspect=3.1, palette='coolwarm')
The x-axis shows the iterations like [0,2,4,8]
, but I want [0,1,2,3,4,5,6,7,8,9]
.
You can refine the number of x-tick labels by first accessing the axis object returned by the factorplot
and then providing a step
size for the tick labels
ax = sns.factorplot(x="Ranking", y="Features", data = meanplot[:9], kind="bar", size=4, aspect=3.1, palette='coolwarm')
ax.set_xticklabels(step=1)
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