Search Results - (( java implementation clustering algorithm ) OR ( program classification tree algorithm ))

Case Slicing Technique for Feature Selection by A. Shiba, Omar A.

“…All these approaches are implemented with RELIEF feature selection approach. The classification accuracy obtained from the CST method is compared to other selected classification methods such as Value Difference Metric (VDM), Pre-Category Feature Importance (PCF), Cross-Category Feature Importance (CCF), Instance-Based Algorithm (IB4), Decision Tree Algorithms such as Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5), Rough Set methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) and Neural Network methods such as the Multilayer method.…”
Get full text
Get full text

Classification of Google Play application using decision tree algorithm on sentiment analysis of text reviews / Aqil Khairy Hamsani, Ummu Fatihah Mohd Bahrin and Wan Dorishah Wan A... by Hamsani, Aqil Khairy, Mohd Bahrin, Ummu Fatihah, Wan Abdul Manan, Wan Dorishah

“…The project's objectives are to study the classifying approach of Google Play Store application reviews using the Decision Tree algorithm, develop a prototype of a classifying application program, and evaluate the accuracy model of the review classification program. …”
Get full text
Get full text
Get full text

Classification model for hotspot occurrences using spatial decision tree algorithm by Sitanggang, Imas Sukaesih, Yaakob, Razali, Mustapha, Norwati, Nuruddin, Ahmad Ainuddin

“…This study describes the application of data mining technique namely decision tree on forest fires data. We improved the ID3 decision tree algorithm such that it can be utilized on spatial data in order to develop a classification model for hotspots occurrence. …”
Get full text
Get full text
Get full text

Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly by Zulkifly, Ahmad Zuladzlan

“…This project will use fuzzy k-means clustering algorithm to cluster the data because it is easy to implement and have many advantages. …”
Get full text
Get full text

Evaluation of data mining classification and clustering techniques for diabetes / Tuba Pala and Ali Yilmaz Camurcu by Pala, Tuba, Camurcu, Ali Yilmaz

“…Multilayer Perceptron algorithm has been the best algorithm with the highest success percentage in both of the programs; Decision Trees has been the algorithm which has the lowest success percentage again in both of the programs. …”
Get full text
Get full text
Get full text

Decision tree method for fault causes classification based on RMS-DWT analysis in 275 kV transmission lines network by Asman, Saidatul Habsah, Ab Aziz, Nur Fadilah, Ungku Amirulddin Al Amin, Ungku Anisa, Ab Kadir, Mohd Zainal Abidin

“…This paper presents a statistical algorithm for classification of fault causes on power transmission lines. …”
Get full text
Get full text

Classification Algorithms to Determine Students’ Specialization in a Higher Education Institution by Tri Basuki, Kurniawan, Indah, Hidayanti

“…After that, we looked at how Python programming classification algorithms like Support Vector Machine (SVM), Naïve Bayes, Random Forest, and Decision Tree performed in classifying the areas of specialization of the students. …”
Get full text
Get full text
Get full text

Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

“…The clustering research is regarding the area of data mining and implementation of the clustering algorithms. …”
Get full text
Get full text
Get full text
Get full text

Predicting Student Performance in Object Oriented Programming Using Decision Tree : A Case at Kolej Poly-Tech Mara, Kuantan by Mohd Hanis, Rani, Abdullah, Embong

“…Using 10-fold cross validation for each algorithm, it was found that decision tree was the best algorithm with 83.6944% correctness. …”
Get full text
Get full text

A Toolkit for Simulation of Desktop Grid Environment by FOROUSHAN, PAYAM CHINI

“…A simulator for desktop grid environment has been developed using Java as the implementation language due to its wide popularity. …”
Get full text
Get full text

A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem by Mohd Pozi, Muhammad Syafiq

“…There are two methods in dealing with imbalanced classification problem, which are based on data or algorithmic level. …”
Get full text
Get full text
Get full text

Decision tree method for fault causes classification based on rms-dwt analysis in 275 kv transmission lines network by Asman S.H., Aziz N.F.A., Amirulddin U.A.U., Kadir M.Z.A.A.

“…This paper presents a statistical algorithm for classification of fault causes on power transmission lines. …”

An efficient and effective case classification method based on slicing by Shiba, Omar A. A., Sulaiman, Md. Nasir, Mamat, Ali, Ahmad, Fatimah

“…The algorithms are: Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5). …”
Get full text
Get full text
Get full text

Lightning fault classification for transmission line using support vector machine by Asman, Saidatul Habsah, Ab Aziz, Nur Fadilah, Ab Kadir, Mohd Zainal Abidin, Ungku Amirulddin, Ungku Anisa, Roslan, Nurzanariah, Elsanabary, Ahmed

“…The proposed method was implemented in the MATLAB/SIMULINK programming platform. The classification performance of the developed algorithms was evaluated using confusion matrix. …”
Get full text
Get full text

Lightning Fault Classification for Transmission Line Using Support Vector Machine by Asman S.H., Aziz N.F.A., Kadir M.Z.A.A., Amirulddin U.A.U., Roslan N., Elsanabary A.

“…The proposed method was implemented in the MATLAB/SIMULINK programming platform. The classification performance of the developed algorithms was evaluated using confusion matrix. …”

Image classification using two dimensional wavelet coefficients with parallel computing by Ong, Yew Fai

“…This research algorithm demonstrated a very promising result with Support Vector Machines, this algorithm produces a 90% of accuracies whereas the decision tree algorithm gets 100% accuracies. …”
Get full text
Get full text

A new mobile botnet classification based on permission and API calls by Yusof M., Madihah Mohd Saudi, Farida Hazwani Mohd Ridzuan

Subjects:

Enhancing Performance of Batik SMEs through Cleaner Production Adoption: Insights from Clustering Algorithm Analysis by Achmad, Fandi, Zulkarnain, Ibnu, Rumanti, Augustina Asih, Wiratmadja, Iwan Inrawan, Shuhidan, Shuhaida Mohamed

Get full text
Get full text

Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining. by Saeed, Walid

“…The accuracy for rules and classification resulted from the TIP method are compared with other methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) from Rough Set, Genetic Algorithm (GA), Johnson reducer, HoltelR method, Multiple Regression (MR), Neural Network (NN), Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5); all other classifiers that are mostly used in the classification tasks. …”
Get full text
Get full text

A web-based implementation of k-means algorithms by Lee, Quan

“…Firstly, k-luster could incorporate additional clustering algorithms, or even classification algorithms in the future. …”
Get full text
Get full text