Nearest Neighbor Classifiers

ثبت نشده
چکیده

The 1-N-N classifier is one of the oldest methods known. The idea is extremely simple: to classify X find its closest neighbor among the training points (call it X ,) and assign to X the label of X .

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Lazy Classifiers Using P-trees

Lazy classifiers store all of the training samples and do not build a classifier until a new sample needs to be classified. It differs from eager classifiers, such as decision tree induction, which build a general model (such as a decision tree) before receiving new samples. K-nearest neighbor (KNN) classification is a typical lazy classifier. Given a set of training data, a knearest neighbor c...

متن کامل

Multiple Views in Ensembles of Nearest Neighbor Classifiers

Multi-view classification is a machine learning methodology when patterns or objects of interest are represented by a set of different views (sets of features) rather than the union of all views. In this paper, multiple views are employed in ensembles of nearest neighbor classifiers where they demonstrate promising results in classifying a challenging data set of protein folds. In particular, u...

متن کامل

Prototype reduction techniques: A comparison among different approaches

The main two drawbacks of nearest neighbor based classifiers are: high CPU costs when the number of samples in the training set is high and performance extremely sensitive to outliers. Several attempts of overcoming such drawbacks have been proposed in the pattern recognition field aimed at selecting/gen-erating an adequate subset of prototypes from the training set. The problem addressed in th...

متن کامل

Learning Nearest-Neighbor Classifiers with Hyperkernels

We consider improving the performance of k-Nearest Neighbor classifiers. A regularized kNN is proposed to learn an optimal dissimilarity function to substitute the Euclidean metric. The learning process employs hyperkernels and shares a similar regularization framework as support vector machines (SVM). Its performance is shown to be consistently better than kNN, and is competitive with SVM.

متن کامل

Identification of selected monogeneans using image processing, artificial neural network and K-nearest neighbor

Abstract Over the last two decades, improvements in developing computational tools made significant contributions to the classification of biological specimens` images to their correspondence species. These days, identification of biological species is much easier for taxonomist and even non-taxonomists due to the development of automated computer techniques and systems.  In this study, we d...

متن کامل

Mixtures of Large Margin Nearest Neighbor Classifiers

The accuracy of the k-nearest neighbor algorithm depends on the distance function used to measure similarity between instances. Methods have been proposed in the literature to learn a good distance function from a labelled training set. One such method is the large margin nearest neighbor classifier that learns a global Mahalanobis distance. We propose a mixture of such classifiers where a gati...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2002