Search Results - ((((slicing algorithm) OR (stemming algorithm))) OR (((mining algorithm) OR (learning algorithm))))
Search alternatives:
- stemming algorithm »
- learning algorithm »
- slicing algorithm »
- mining algorithm »
-
1
Case Slicing Technique for Feature Selection
Published 2004“…One of the problems addressed by machine learning is data classification. Finding a good classification algorithm is an important component of many data mining projects. …”
Get full text
Get full text
Thesis -
2
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 -
3
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 -
4
Analyzing enrolment patterns: modified stacked ensemble statistical learning based approach to educational decision-making
Published 2024“…Moreover, the introduction of the novel modified stacked ensemble statistical learning-based algorithm had improved predictive accuracy compared to traditional dichotomous logistic regression algorithms on average, particularly at optimal training-to-test ratios of 70:30, 80:20, and 90:10. …”
Get full text
Get full text
Get full text
Article -
5
Position score weighting technique for mining web content outliers.
Published 2013“…The existing mining web content outlier methods used stemming algorithm to preprocess the web documents and leave the domain dictionary in their root words. …”
Get full text
Get full text
Get full text
Article -
6
Predicting students’ STEM academic performance in Malaysian secondary schools using educational data mining
Published 2023“…Four different data mining classification algorithms which are Random Forest, PART, J48 and Naive Bayes will be used on the dataset. …”
Get full text
Get full text
Thesis -
7
Web Usage Mining for UUM Learning Care Using Association Rules
Published 2004“…In order to produce the university E-Learning (UUM Educare) portal usage patterns and user behaviors, this paper implements the high level process of Web usage mining using basic Association Rules algorithm - Apriori Algorithm. …”
Get full text
Get full text
Get full text
Thesis -
8
Web usage mining for UUM learning care using association rules
Published 2004“…With the powerful of data mining technique, Web usage mining approach has been combined with the basic Association Rules, Apriori Algorithm to optimize the content of the university E�Learning portal. …”
Get full text
Get full text
Thesis -
9
Machine Learning Algorithms for Diabetes Prediction: A Review Paper
Published 2023“…Computer aided diagnosis; Data mining; Learning systems; Patient treatment; Predictive analytics; Robotics; Support vector machines; Data mining algorithm; Diabetes mellitus; Early diagnosis; Knowledge accumulation; Literature reviews; Prediction techniques; Review papers; Support vector machine algorithm; Learning algorithms…”
Conference Paper -
10
An improved diagnostic algorithm based on deep learning for ischemic stroke detection in posterior fossa
Published 2020“…The algorithm framework consists of hybrid of improved Xception model and YOLO V2 detector to classify the PF slices with ischemic and localise the infarction in classified slices, respectively. …”
Get full text
Get full text
Get full text
Get full text
Thesis -
11
Single Slice Grouping Mechanism for Recognition of Cursive Handwritten Courtesy Amounts of Malaysian Bank Cheques
Published 2003“…A three layer neural Network architecture with the new error function of Backpropagation learning algorithm is used. This approach yields good recognition results with faster convergence rates.…”
Get full text
Get full text
Article -
12
Sentiment mining using immune network algorithm /Raja Muhammad Hafiz Raja Kamarudin
Published 2012“…The results obtained by utilizing Immune Network in sentiment mining are not very impressive compared to other Machine Learning algorithms. …”
Get full text
Get full text
Thesis -
13
Privacy Preserving Features Selection for Data Mining using Machine Learning Algorithms
Published 2023“…Data Analytics; Data mining; Decision making; Feature extraction; Machine learning; Predictive analytics; Privacy by design; Features selection; Fine grains; No leakages; Predictive modeling; Privacy preserving; Learning algorithms…”
Conference Paper -
14
Accelerated mine blast algorithm for ANFIS training for solving classification problems
Published 2016“…Mine Blast Algorithm (MBA) is newly developed metaheuristic technique. …”
Get full text
Get full text
Article -
15
An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…In the second phase, a classifier ensemble learning model is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on Binary Quantum Gravitational Search Algorithm (QBGSA), (ii) To mine data streams using various data chunks and overcome a failure of single classifiers based on SVM, MLP and K-NN algorithms. …”
Get full text
Get full text
Thesis -
16
IncSPADE: An Incremental Sequential Pattern Mining Algorithm Based on SPADE Property
Published 2016“…In this paper we propose Incremental Sequential PAttern Discovery using Equivalence classes (IncSPADE) algorithm to mine the dynamic database without the requirement of re-scanning the database again. …”
Get full text
Get full text
Get full text
Book Chapter -
17
Evaluations of oil palm fresh fruit bunches maturity degree using multiband spectrometer
Published 2017“…Furthermore, the Lazy-IBK algorithm have been validated to produce the best classifier model, with the machine learning algorithm performance of 65.26%, recall of 65.3%, and 65.4% F-measured as compared to other evaluated machine learning classifier algorithms proposed within the WEKA data mining algorithm. …”
Get full text
Get full text
Get full text
Thesis -
18
Frequent Lexicographic Algorithm for Mining Association Rules
Published 2005“…The Flex algorithm and the other two existing algorithms Apriori and DIC under the same specification are tested toward these datasets and their extraction times for mining frequent patterns were recorded and compared. …”
Get full text
Get full text
Thesis -
19
DATA CLASSIFICATION SYSTEM WITH FUZZY NEURAL BASED APPROACH
Published 2005“…The project's objective is identifying the available data mining algorithms in data classification and applying new data mining algorithm to perform classification tasks. …”
Get full text
Get full text
Final Year Project -
20
Predicting STEM academic performance in secondary schools: data mining approach
Published 2019“…Three different data mining classification algorithms which are Decision Tree (DT), Artificial Neural Networks (ANN), and Naive Bayes (NB) will be used on the dataset. …”
Get full text
Get full text
Get full text
Conference or Workshop Item