SKILLSHARE ARTIFICIAL INTELLIGENCE ACADEMY 5 KNEAREST NEIGHBOR CLASSIFICATION METHOD-iLLiTERATE
Submitted by milohaze on Thu, 03/28/2019 - 13:33
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In pattern recognition, the k-nearest neighbors algorithm (k-NN) is a non-parametric method used for classification and regression.
k-NN is a type of instance-based learning, or lazy learning, where the function is only approximated locally and all computation is deferred until classification. The k-NN algorithm is among the simplest of all machine learning algorithms.
For classification, a useful technique can be to assign weight to the contributions of the neighbors, so that the nearer neighbors contribute more to the average than the more distant ones.
The neighbors are taken from a set of objects for which the class (for k-NN classification). This can be thought of as the training set for the algorithm, though no explicit training step is required.
In this course you learn how to classify datasets by k-Nearest Neighbors Classification Method to find the correct class for data and reduce error.
You learn how to use python to estimate output of your system. In this section you can classify:
- Python Dataset
- IRIS Flowers
- Make your own k Nearest Neighbors Algorithm
k-NN is a type of instance-based learning, or lazy learning, where the function is only approximated locally and all computation is deferred until classification. The k-NN algorithm is among the simplest of all machine learning algorithms.
For classification, a useful technique can be to assign weight to the contributions of the neighbors, so that the nearer neighbors contribute more to the average than the more distant ones.
The neighbors are taken from a set of objects for which the class (for k-NN classification). This can be thought of as the training set for the algorithm, though no explicit training step is required.
In this course you learn how to classify datasets by k-Nearest Neighbors Classification Method to find the correct class for data and reduce error.
You learn how to use python to estimate output of your system. In this section you can classify:
- Python Dataset
- IRIS Flowers
- Make your own k Nearest Neighbors Algorithm