KNeighborsClassifier
KNeighborsClassifier# class sklearn.neighbors.KNeighborsClassifier(n_neighbors=5, *, weights='uniform', algorithm='auto', leaf_size=30, p=2, metric='minkowski', metric_params=None, n_jobs=None)[source]# Classifier implementing the k-nearest neighbors vote. Read more in the User Guide. Parameters: n_neighborsint, default=5Number of neighbors to use by default for kneighbors queries. weights{‘unifor
Building Decision Tree Algorithm in Python with scikit learn - Dataaspirant
Decision Tree Algorithm implementation with scikit learn One of the cutest and lovable supervised algorithms is Decision Tree Algorithm. It can be used for both the classification as well as regression purposes also. As in the previous article how the decision tree algorithm works we have given the enough introduction to the working aspects of decision tree algorithm. In this article, we are going
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