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Date Fruit Classification using K-Nearest Neighbor with Principal Component Analysis and Binary Particle Swarm Optimization
Various cultivars of date fruit distributed throughout exhibit diverse complexity and unique attributes, including color, flavor,
shape, and texture. These distinctive characteristics and appearance occasionally may lack variability in date fruits,…
shape, and texture. These distinctive characteristics and appearance occasionally may lack variability in date fruits,…
Combination of K-NN and PCA Algorithms on Image Classification of Fish Species
To do fish farming, you need to know the types of fish to be cultivated. This is because the type of fish will affect how it is
handled and managed. So, this study aims to develop an image processing system for classifying fish species, especially…
handled and managed. So, this study aims to develop an image processing system for classifying fish species, especially…
A Bonferroni Mean Based Fuzzy K-Nearest Centroid Neighbor Classifier
K-nearest neighbor (KNN) is an effective nonparametric classifier that determines the neighbors of a point based only on distance proximity. The classification performance of KNN is disadvantaged by the presence of outliers in small sample size…
TELKOMNIKA Telecommunication Computing Electronics and Control
Big data classification based on improved parallel k-nearest neighbor
In response to the rapid growth of many sorts of information, highway data
has continued to evolve in the direction of big data in terms of scale, type,
and structure, exhibiting characteristics of multi-source heterogeneous data.
The k-nearest…
has continued to evolve in the direction of big data in terms of scale, type,
and structure, exhibiting characteristics of multi-source heterogeneous data.
The k-nearest…
TELKOMNIKA Telecommunication, Computing, Electronics and Control
Convolutional neural network for maize leaf disease image classification
This article discusses the maize leaf disease image classification.
The experimental images consist of 200 images with 4 classes: healthy,
cercospora, common rust and northern leaf blight. There are 2 steps: feature extraction and classification.…
The experimental images consist of 200 images with 4 classes: healthy,
cercospora, common rust and northern leaf blight. There are 2 steps: feature extraction and classification.…
Kombinasi K-Nearest Neighbor(KNN) dan Relief-F Untuk Meningkatkan Akurasi Pada Klasifikasi Data
Dalam penelitian ini, penulis mengusulkan proses peningkatan akurasi pada K-Nearest
Neighbor (KNN) dengan kombinasi seleksi fitur menggunakan metode Relief-F. Adapun
penyebab kurang maksimalnya akurasi pada K-Nearest Neighbor dibandingkan dengan…
Neighbor (KNN) dengan kombinasi seleksi fitur menggunakan metode Relief-F. Adapun
penyebab kurang maksimalnya akurasi pada K-Nearest Neighbor dibandingkan dengan…