Search Results - (( develop missing tree algorithm ) OR ( java application mining algorithm ))
Search alternatives:
- application mining »
- java application »
- mining algorithm »
- tree algorithm »
- develop »
-
1
Direct approach for mining association rules from structured XML data
Published 2012Get full text
Get full text
Thesis -
2
Enhanced mechanism to handle missing data of Hadith classifier
Published 2011Get full text
Get full text
Get full text
Proceeding Paper -
3
Crown counting and mapping of missing oil palm tree using airborne imaging system
Published 2019“…The overall accuracy of counting existing oil palm trees using the approach developed in this study is 93.3% while missing trees detection gives the detection accuracy of 89.2%. …”
Get full text
Get full text
Thesis -
4
-
5
Detecting Remote-To-Local (R2L) attack using Decision Tree algorithm / Ahmad Nasreen Aqmal Mohd Nordin
Published 2024“…The project successfully achieves its predetermined objectives, culminating in the development of an effective Remote to Local (R2L) Intrusion Detection System utilizing the Decision Tree algorithm. …”
Get full text
Get full text
Thesis -
6
Study and Implementation of Data Mining in Urban Gardening
Published 2019“…Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. These data are processed and stored in appropriate formats in a MySQL server database. …”
Get full text
Get full text
Get full text
Article -
7
Intelligent imputation method for mix data-type missing values to improve data quality
Published 2024“…The significance of this research is to develop an intelligent method that can deal with both missing values and accuracy in large datasets while minimizing time consumed. …”
Get full text
Get full text
Get full text
Thesis -
8
New Learning Models for Generating Classification Rules Based on Rough Set Approach
Published 2000“…Recently, different models were used to generate knowledge from vague and uncertain data sets such as induction decision tree, neural network, fuzzy logic, genetic algorithm, rough set theory, and others. …”
Get full text
Get full text
Thesis -
9
Mining Sequential Patterns Using I-PrefixSpan
Published 2007“…Sequential pattern mining is a relatively new data-mining problem with many areas of application. …”
Get full text
Get full text
Get full text
Conference or Workshop Item -
10
A web-based implementation of k-means algorithms
Published 2022“…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
Get full text
Get full text
Final Year Project / Dissertation / Thesis -
11
Tangible interaction learning model to enhance learning activity processes among children with dyslexia
Published 2024“…The significance of this research is to develop an intelligent method that can deal with both missing values and accuracy in large datasets while minimizing time consumed. …”
Get full text
Get full text
Get full text
Thesis -
12
Mining Sequential Patterns using I-PrefixSpan
Published 2008Get full text
Get full text
Citation Index Journal -
13
Design and performance analysis of a fast 4-way set associative cache controller using Tree Pseudo Least Recently Used algorithm
Published 2023“…A key feature of this design is the incorporation of the Tree Pseudo Least Recently Used (PLRU) algorithm for cache replacement, a strategic choice aimed at optimizing cache performance. …”
Get full text
Get full text
Get full text
Get full text
Article -
14
Improving performance of automated coronary arterial tree center-line extraction, stent localization and tracking
Published 2012“…Over the last decade, many algorithms have been developed to address this problem. …”
Get full text
Get full text
Thesis -
15
Bayesian random forests for high-dimensional classification and regression with complete and incomplete microarray data
Published 2018“…These weights are in turn used to develop new impurity functions for selecting optimal splits for each tree in a forest. …”
Get full text
Get full text
Get full text
Get full text
Thesis -
16
Data Mining Analysis Of Chronic Kidney Disease (CKD) Level
Published 2022“…Adding the uncertain class the best accuracy obtained was 98.5% using the SMO algorithm. A predictive classification model that determines the accuracy for three classification classes was developed accordingly using the SMO algorithm.…”
Get full text
Get full text
Monograph -
17
Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. The proposed model will be tested and evaluated on both NSL-KDD and KDD-CUP 99 using several performance metrics.…”
Get full text
Get full text
Thesis -
18
Analysis of hyperspectral reflectance for disease classification of soybean frogeye leaf spot using Knime analytics
Published 2023“…This analysis involved the implementation of machine learning (ML) algorithms, including decision trees, random forests, and stacking, to classify soybean FLS severity levels. …”
Get full text
Get full text
Article -
19
Diamond price prediction using random forest algorithm / Nur Amirah Mohd Azmi
Published 2025“…Some of the broad steps of methodology involve data preprocessing, by means of which handling of missing values, outliers, and inconsistencies for quality were developed. …”
Get full text
Get full text
Thesis -
20
Finding an effective classification technique to develop a software team composition model
Published 2017“…Ineffective software team composition has become recognized as a prominent aspect of software project failures.Reports from results extracted from different theoretical personality models have produced contradicting fits, validity challenges, and missing guidance during software development personnel selection.It is also believed that the technique/s used while developing a model can impact the overall results.Thus, this study aims to: 1) discover an effective classification technique to solve the problem, and 2) develop a model for composition of the software development team.The model developed was composed of three predictors: team role, personality types, and gender variables; it also contained one outcome: team performance variable.The techniques used for model development were logistic regression, decision tree, and Rough Sets Theory (RST).Higher prediction accuracy and reduced patte rn complexity were the two parameters forselecting the effective technique.Based on the results, the Johnson Algorithm (JA) of RST appeared to be an effective technique for a team composition model.The study has proposed a set of 24 decision rules for finding effective team members.These rules involve gender classification to highlight the appropriate personality profile for software developers.In the end, this study concludes that selecting an appropriate classification technique is one of the most important factors in developing effective models.…”
Get full text
Get full text
Get full text
Article
