Face Recognition Using Isomap, KNN and Naïve Bayes Classifier
نویسندگان
چکیده
Sistem pengenalan wajah merupakan sistem yang dapat mengenali seseorang dengan bantuan komputer. Untuk tersebut, dilakukan ekstraksi fitur terlebih dahulu. Pada penelitian ini digunakan metode isomap untuk mengekstrak wajah. Isomap suatu mengubah dimensi citra berdimensi tinggi menjadi fitur-fitur memiliki rendah. Data adalah diperoleh dari 6 orang, setiap orang 4 variasi ekspresi citra. Setelah diekstrak, selanjutnya klasifikasi menggunakan K Nearest Neighbor (KNN) dan Naive Bayes Classifier. Berdasarkan hasil pada KNN, tingkat akurasi terbaik terjadi saat jumlah tetangga = 2. Nilai sebesar 87,5%, nilai rata-rata presisi terbobot (RPT) 81,25% recall (RRT) 87,5% Classifier 50%, 62% 50%.
منابع مشابه
Image Classification Using Naïve Bayes Classifier
An image classification scheme using Naïve Bayes Classifier is proposed in this paper. The proposed Naive Bayes Classifier-based image classifier can be considered as the maximum a posteriori decision rule. The Naïve Bayes Classifier can produce very accurate classification results with a minimum training time when compared to conventional supervised or unsupervised learning algorithms. Compreh...
متن کاملFace Recognition Using Bagging Knn
In this paper a novel ensemble based techniques for face recognition is presented. In ensemble learning a group of methods are employed and their results are combined to form the final results of the system. Gaining the higher accuracy rate is the main advantage of this system. Two of the most successful wrapping classification methods are bagging and boosting. In this paper we used the K neare...
متن کاملThe Impact of Feature Extraction on the Performance of a Classifier: kNN, Naïve Bayes and C4.5
“The curse of dimensionality” is pertinent to many learning algorithms, and it denotes the drastic raise of computational complexity and the classification error in high dimensions. In this paper, different feature extraction techniques as means of (1) dimensionality reduction, and (2) constructive induction are analyzed with respect to the performance of a classifier. Three commonly used class...
متن کاملSemantic Naïve Bayes Classifier for Document Classification
In this paper, we propose a semantic naïve Bayes classifier (SNBC) to improve the conventional naïve Bayes classifier (NBC) by incorporating “document-level” semantic information for document classification (DC). To capture the semantic information from each document, we develop semantic feature extraction and modeling algorithms. For semantic feature extraction, we first apply a log-Bilinear d...
متن کاملBoosting the Tree Augmented Naïve Bayes Classifier
The Tree Augmented Naïve Bayes (TAN) classifier relaxes the sweeping independence assumptions of the Naïve Bayes approach by taking account of conditional probabilities. It does this in a limited sense, by incorporating the conditional probability of each attribute given the class and (at most) one other attribute. The method of boosting has previously proven very effective in improving the per...
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: Cogito smart journal
سال: 2023
ISSN: ['2541-2221', '2477-8079']
DOI: https://doi.org/10.31154/cogito.v9i1.473.38-47