Performances of k-means clustering algorithm with different distance metrics
TM Ghazal - Intelligent Automation & Soft …, 2021 - research.skylineuniversity.ac.ae
Clustering is the process of grouping the data based on their similar properties. Meanwhile,
it is the categorization of a set of data into similar groups (clusters), and the elements in each …
it is the categorization of a set of data into similar groups (clusters), and the elements in each …
Perbandingan akurasi euclidean distance, minkowski distance, dan manhattan distance pada algoritma K-Means clustering berbasis Chi-Square
M Nishom - Jurnal Informatika: Jurnal Pengembangan …, 2019 - ejournal.poltekharber.ac.id
Dalam data mining, terdapat beberapa algoritma yang sering digunakan dalam
pengelompokan data, diantaranya adalah K-Means. Namun, metode tersebut masih …
pengelompokan data, diantaranya adalah K-Means. Namun, metode tersebut masih …
Comparing the performance of L* A* B* and HSV color spaces with respect to color image segmentation
Color image segmentation is a very emerging topic for image processing research. Since it
has the ability to present the result in a way that is much more close to the human yes …
has the ability to present the result in a way that is much more close to the human yes …
A new combination of artificial neural network and K-nearest neighbors models to predict blast-induced ground vibration and air-overpressure
M Amiri, H Bakhshandeh Amnieh… - Engineering with …, 2016 - Springer
Blasting operation is widely used method for rock excavation in mining and civil works.
Ground vibration and air-overpressure (AOp) are two of the most detrimental effects induced …
Ground vibration and air-overpressure (AOp) are two of the most detrimental effects induced …
Comparative analysis of inter-centroid K-Means performance using euclidean distance, canberra distance and manhattan distance
M Faisal, EM Zamzami - Journal of Physics: Conference Series, 2020 - iopscience.iop.org
Clustering is a method needed to group data or objects based on the required level between
data, K-means is one of the clustering methods used that can be used easily in its …
data, K-means is one of the clustering methods used that can be used easily in its …
[图书][B] Machine learning approaches in cyber security analytics
T Thomas, AP Vijayaraghavan, S Emmanuel - 2020 - Springer
With an overwhelming amount of data being generated and transferred over various
networks, cybersecurity experts are having a hard time in monitoring everything that gets …
networks, cybersecurity experts are having a hard time in monitoring everything that gets …
[PDF][PDF] Reduksi atribut menggunakan information gain untuk optimasi cluster algoritma k-means
JEPIN Page 1 JEPIN (Jurnal Edukasi dan Penelitian Informatika) ISSN(e): 2548-9364 / ISSN(p)
: 2460-0741 Vol. 6 No. 1 April 2020 Submitted 16-11-2019; Revised 26-03-2020; Accepted …
: 2460-0741 Vol. 6 No. 1 April 2020 Submitted 16-11-2019; Revised 26-03-2020; Accepted …
Ensemble feature selection using distance-based supervised and unsupervised methods in binary classification
B Hallajian, H Motameni, E Akbari - Expert Systems with Applications, 2022 - Elsevier
Feature selection refers to the problem of finding the optimal subset of features by removing
irrelevant and redundant features to improve classification accuracy. The determination of …
irrelevant and redundant features to improve classification accuracy. The determination of …
Towards modified entropy mutual information feature selection to forecast medium-term load using a deep learning model in smart homes
Over the last decades, load forecasting is used by power companies to balance energy
demand and supply. Among the several load forecasting methods, medium-term load …
demand and supply. Among the several load forecasting methods, medium-term load …
A clustering approach to identify multidimensional poverty indicators for the bottom 40 percent group
M Abdul Rahman, NS Sani, R Hamdan, Z Ali Othman… - PloS one, 2021 - journals.plos.org
The Multidimensional Poverty Index (MPI) is an income-based poverty index which
measures multiple deprivations alongside other relevant factors to determine and classify …
measures multiple deprivations alongside other relevant factors to determine and classify …