Search Results - (( java implementation graph algorithm ) OR ( programming program bayes algorithm ))
Search alternatives:
- implementation graph »
- java implementation »
- programming program »
- graph algorithm »
- bayes algorithm »
- program bayes »
-
1
-
2
Implementation of locust inspired scheduling algorithm with huge number of servers for energy efficiency in a cloud datacenter
Published 2019“…In the benchmark paper, the result of implementation of LACE algorithm in 400, 600, 800 and 1000 servers were plotted at different graphs. …”
Get full text
Get full text
Thesis -
3
Classification Algorithms to Determine Students’ Specialization in a Higher Education Institution
Published 2023“…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
Article -
4
Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization
Published 2019“…In this system, the layout was designed under two categories which are the standard bay size and the small bay size to increase the parking bays. …”
Get full text
Get full text
Thesis -
5
Sentiment mining in twitter for early depression detection / Najihah Salsabila Ishak
Published 2021“…A classifier model is developed using Naive Bayes characteristics. A comparison between built-in Scikit Learn Naive Bayes algorithm, and the scratch Naive Bayes algorithm is used to measure its effectiveness in terms of accuracy. …”
Get full text
Get full text
Thesis -
6
Divorce prediction using Naive Bayes / Alia Hannani Ahmad Bakri
Published 2024Get full text
Get full text
Thesis -
7
Novice programmers’ emotion and competency assessments using machine learning on physiological data / Fatima Jannat
Published 2022“…This work investigates the suitability and effectiveness of machine learning algorithms such as Multinomial Naive Bayes, KNN, Logistic Regression, Decision Tree for predicting levels of arousal intensity among the programmers and LSTM deep learning algorithm to classify the programmers according to their performance. …”
Get full text
Get full text
Get full text
Thesis -
8
Evaluation of data mining classification and clustering techniques for diabetes / Tuba Pala and Ali Yilmaz Camurcu
Published 2014“…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
Article -
9
-
10
-
11
Car recognition using Bayes Classifier / Nur Atiqah Mat Samadi
Published 2017Get full text
Get full text
Thesis -
12
-
13
Case Slicing Technique for Feature Selection
Published 2004“…CST was compared to other selected classification methods based on feature subset selection such as Induction of Decision Tree Algorithm (ID3), Base Learning Algorithm K-Nearest Nighbour Algorithm (k-NN) and NaYve Bay~sA lgorithm (NB). …”
Get full text
Get full text
Thesis -
14
-
15
-
16
Mobile app of mood prediction based on menstrual cycle using machine learning algorithm / Nur Hazirah Amir
Published 2019“…It implemented Supervised Learning algorithm with Bayes’ Theorem model for the calculation of mood prediction using Python programming language. …”
Get full text
Get full text
Thesis -
17
Towards a better feature subset selection approach
Published 2010“…The selection of the optimal features subset and the classification has become an important issue in the data mining field.We propose a feature selection scheme based on slicing technique which was originally proposed for programming languages.The proposed approach called Case Slicing Technique (CST).Slicing means that we are interested in automatically obtaining that portion 'features' of the case responsible for specific parts of the solution of the case at hand.We show that our goal should be to eliminate the number of features by removing irrelevant once.Choosing a subset of the features may increase accuracy and reduce complexity of the acquired knowledge.Our experimental results indicate that the performance of CST as a method of feature subset selection is better than the performance of the other approaches which are RELIEF with Base Learning Algorithm (C4.5), RELIEF with K-Nearest Neighbour (K-NN), RELIEF with Induction of Decision Tree Algorithm (ID3) and RELIEF with Naïve Bayes (NB), which are mostly used in the feature selection task.…”
Get full text
Get full text
Get full text
Conference or Workshop Item -
18
Priority and dynamic quantum time algorithms for central processing unit scheduling
Published 2018“…The proposed algorithms (Priority Dynamic Quantum Time and Multi Priority Dynamic Quantum Time Algorithms) are implemented using JAVA programming language and validated using Key Performance Indicators equations. …”
Get full text
Get full text
Thesis -
19
-
20