from mlxtend.plotting import plot_decision_regions def knn_comparision(data, k): X = data[['x1','x2']].values y = data['y'].astype(int).values clf = neighbors.KNeighborsClassifier(n_neighbors=k) clf.fit(X, y) # Plotting decision regions plot_decision_regions(X, y, clf=clf, legend=2)
What are the parameters ‘clf‘ and ‘legend‘ in plot_decision_regions?
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Answer
clf
is the classifier object being returned from neighbors.KNeighborsClassifier
, which is likely coming from sklearn.
BigBen linked the documentation already for the plot_decision_regions
function, which explains what they do.