Search Results - (( program case tree algorithm ) OR ( java application modified algorithm ))
Search alternatives:
- application modified »
- java application »
- tree algorithm »
- program case »
- case tree »
-
1
Case Slicing Technique for Feature Selection
Published 2004“…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
Thesis -
2
Predicting Student Performance in Object Oriented Programming Using Decision Tree : A Case at Kolej Poly-Tech Mara, Kuantan
Published 2013Get full text
Get full text
Conference or Workshop Item -
3
Designing of disparity map based on hierarchical dynamic programming using satellite stereo imagery
Published 2023Conference Paper -
4
Direct approach for mining association rules from structured XML data
Published 2012Get full text
Get full text
Thesis -
5
An efficient and effective case classification method based on slicing
Published 2006“…The algorithms are: Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5). …”
Get full text
Get full text
Get full text
Article -
6
Designing of disparity map based on hierarchical dynamic programming using satellite stereo imagery
Published 2016“…Electric supply companies monitor the vegetation/trees near power lines to avoid the blackouts that may occur in case of an improper monitoring of vegetation. …”
Get full text
Get full text
Conference or Workshop Item -
7
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 -
8
Prevention And Detection Mechanism For Security In Passive Rfid System
Published 2013“…A GUI is created in a form of JAVA application to display data detected from tag. …”
Get full text
Get full text
Thesis -
9
Automatic generation of content security policy to mitigate cross site scripting
Published 2016“…The algorithm is implemented as a plugin. It does not interfere with the web application original code. …”
Get full text
Get full text
Conference or Workshop Item -
10
-
11
Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.
Published 2005“…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
Thesis -
12
-
13
Energy-aware task scheduling for streaming applications on NoC-based MPSoCs
Published 2024“…Our approach is supported by a set of novel techniques, which include constructing an initial schedule based on a list scheduling where the priority of each task is its approximate successor-tree-consistent deadline such that the workload across all the processors is balanced, a retiming heuristic to transform intraperiod dependencies into inter-period dependencies for enhancing parallelism, assigning an optimal discrete frequency for each task and each message using a Non-Linear Programming (NLP)-based algorithm and an Integer-Linear Programming (ILP)-based algorithm, and an incremental approach to reduce the memory usage of the retimed schedule in case of memory size violations. …”
Get full text
Get full text
Get full text
Article -
14
Adaptive persistence layer for synchronous replication (PLSR) in heterogeneous system
Published 2011“…The PLSR architecture model, workflow and algorithms are described. The PLSR has been developed using Java Programming language. …”
Get full text
Get full text
Thesis -
15
Ensemble deep learning approach for apple fruitlet detection from digital images
Published 2024Get full text
Get full text
Get full text
Conference or Workshop Item -
16
-
17
-
18
Propositional satisfiability method in rough classification modeling for data mining
Published 2002“…Two models, Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) to represent the minimal reduct computation problem were proposed. …”
Get full text
Get full text
Thesis -
19