Indonesian Grapes are a vine. This fruit is often found in markets, shops, and the roadside. Along with development of computer technology today, computers can solve problems by classifying objects objects. How to apply GLCM K-NN methods for classification grapes. The purpose this study dataset used from kaggle.com sources, data tested 3 types grapes, number images 2624. that will be collection...

Machine learning and pattern recognition are the most popular artificial intelligence techniques to model systems, those can learn from data. These techniques efficiently help in Classification, Regression, Clustering and Anomaly detection etc. k-Nearest Neighbors, Parzen Windows and Support Vector Machine (SVM) are some of the widely used Machine Learning classification techniques. This projec...

Prototype generation techniques have arisen as very competitive methods for enhancing the nearest neighbor classifier through data reduction. A great number of methods tackling the prototype generation problem have been proposed in the literature. This technical report provides a survey of the most representative algorithms developed so far. A previously proposed categorization has been used to...

Classification of spatial data has become important due to the fact that there are huge volumes of spatial data now available holding a wealth of valuable information. In this paper we consider the classification of spatial data streams, where the training dataset changes often. New training data arrive continuously and are added to the training set. For these types of data streams, building a ...

Classification learning applies to a wide range of tasks, from diagnosis and troubleshooting to pattern recognition and keyword assignment. Many methods have been used to build classification systems, including artificial neural networks, rule-based expert systems (both hand-built and inductively learned), fuzzy rule systems, memorybased and case-based systems and nearest neighbor systems, gene...

Classification based on k-nearest neighbors (kNN classification) is one of the most widely used classification methods. The number k of nearest neighbors used for achieving a high accuracy in classification is given in advance and is highly dependent on the data set used. If the size of data set is large, the sequential or binary search of NNs is inapplicable due to the increased computational ...