Klasifikasi Jenis Buah Jambu Biji Menggunakan Algoritma Principal Component Analysis dan K-Nearest Neighbor
نویسندگان
چکیده
The maturity level of guava fruit can be determined by looking at various factors. Shape is one the factors that play a role in identifying certain objects. classification seen from shape, texture and color. shape quite diverse ranging round (Round shape) to oval (Pear shape). So Matlab application was built determine type based on its color, texture. K-Nearest Neighbor classify objects learning data closest object so results more accurate. Principal Component Analysis (PCA) statistical technique for simplifying many-dimensional sets into lower dimensions (extration features). combination with produces fairly high accuracy determining using total 45 images divided two including training 36 test 9 data.
منابع مشابه
Klasifikasi Data Cardiotocography Dengan Integrasi Metode Neural Network Dan Particle Swarm Optimization
Backpropagation (BP) adalah sebuah metode yang digunakan dalam training Neural Network (NN) untuk menentukan parameter bobot yang sesuai. Proses penentuan parameter bobot dengan menggunakan metode backpropagation sangat dipengaruhi oleh pemilihan nilai learning rate (LR)-nya. Penggunaan nilai learning rate yang kurang optimal berdampak pada waktu komputasi yang lama atau akurasi klasifikasi yan...
متن کاملDrought Monitoring and Prediction using K-Nearest Neighbor Algorithm
Drought is a climate phenomenon which might occur in any climate condition and all regions on the earth. Effective drought management depends on the application of appropriate drought indices. Drought indices are variables which are used to detect and characterize drought conditions. In this study, it was tried to predict drought occurrence, based on the standard precipitation index (SPI), usin...
متن کاملFast Approximate Nearest-Neighbor Search with k-Nearest Neighbor Graph
We introduce a new nearest neighbor search algorithm. The algorithm builds a nearest neighbor graph in an offline phase and when queried with a new point, performs hill-climbing starting from a randomly sampled node of the graph. We provide theoretical guarantees for the accuracy and the computational complexity and empirically show the effectiveness of this algorithm.
متن کاملAutomatic Face Classiication Using Principal Component Analysis and Nearest Neighbor Classiication 2 Related Work
1 Problem deenition In the recent years there has been a growing interest in automatic face recognition and classiication systems. Computational models of face recognition, in particular are interesting becaause they can contribute not only to theoretical insights but also to practical applications such as criminal identiication, security systems, image and lm processing and human-computer inte...
متن کاملUnsupervised K-Nearest Neighbor Regression
In many scientific disciplines structures in highdimensional data have to be found, e.g., in stellar spectra, in genome data, or in face recognition tasks. In this work we present a novel approach to non-linear dimensionality reduction. It is based on fitting K-nearest neighbor regression to the unsupervised regression framework for learning of low-dimensional manifolds. Similar to related appr...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Generation Journal
سال: 2023
ISSN: ['2549-2233', '2580-4952']
DOI: https://doi.org/10.29407/gj.v7i1.17900