Search Results - (( data application testing algorithm ) OR ( data classification techniques algorithm ))
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1
Classification of credit card holder behavior using K Nearest Neighbor algorithm / Ahmad Faris Rahimi
Published 2017“…Testing of the application are using 10-Fold Cross Validation technique. 90% of the data be used as a training and another 10% be used for the testing part. …”
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2
A Study On Gene Selection And Classification Algorithms For Classification Of Microarray Gene Expression Data
Published 2005“…Gene Selection Plays An Important Role Prior To Tissue Classification. In This Paper, A Study On Numerous Combinations Of Gene Selection Techniques And Classification Algorithms For Classification Of Microarray Gene Expression Data Is Presented. …”
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Article -
3
Grid-Based Classifier as a Replacement for Multiclass Classifier in a Supervised Non-Parametric Approach
Published 2009“…The quality of a given classification technique is measured by the computational complexity, execution time of algorithms, and the number of patterns that can be classified correctly despite any distribution. …”
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4
An improved data classification framework based on fractional particle swarm optimization
Published 2019“…Hence, the proposed technique can be employed to improve the overall classification accuracy and reduce the computational time in data classification applications.…”
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5
Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms
Published 2005“…In cluster generating process, the developed BBSI algorithm was used to select the best band combination for generating cluster by using Iterative self- Organizing Data Analysis (ISODATA) technique. …”
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6
A hybrid approach for artificial immune recognition system / Mahmoud Reza Saybani
Published 2016“…Various data mining techniques are being used by researchers of different domains to analyze data and extract valuable information from a data set for further use. …”
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7
Classification model for hotspot occurrences using spatial decision tree algorithm
Published 2013“…This study describes the application of data mining technique namely decision tree on forest fires data. …”
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8
Spatial Clustering Algorithm for Time Series Rainfall Data Using X-Means Data Splitting
Published 2017“…The proposed algorithm is compared with five types of data transformation techniques, namely mean and median in monthly data and the rest is in daily data such as binary, cumulative and actual values.Results indicate that data transformation using X-means data splitting in hierarchical clustering outperformed other transformation techniques and more consistent between training and testing datasets based on similarity measures.…”
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9
Immune Multiagent System for Network Intrusion Detection using Non-linear Classification Algorithm
Published 2010“…Classification techniques using k-nearest neighbor (k-NN) or Gaussian Mixture (GMM) almost have the common sense that they believe the neighboring data. …”
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Citation Index Journal -
10
Effective gene selection techniques for classification of gene expression data
Published 2005“…Receiver operating characteristic (ROC) score is used to analyze the results. Colon data with 2000 genes and 62 tissue samples is used for the testing. …”
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11
Multilingual Sentiment Analysis From Students Feedback: Optimal Techniques And Resources For Bengali Lingual Data
Published 2024thesis::doctoral thesis -
12
Intent-IQ: customer’s reviews intent recognition using random forest algorithm
Published 2025“…Two machine learning model is chosen to build the classification models which are Random Forest (RF) algorithm and Multinomial Naïve Bayes (MNB) algorithm. …”
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13
Predicting Customer Buying Decisions for Online Shopping with Unbalanced Data Set
Published 2022“…Data pre-processing on the data set may improve the classification results. …”
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Final Year Project / Dissertation / Thesis -
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A novel hybrid classification model of genetic algorithms, modified k-Nearest Neighbor and developed backpropagation neural network
Published 2014“…Among numerous artificial intelligence approaches, k-Nearest Neighbor algorithms, genetic algorithms, and artificial neural networks are considered as the most common and effective methods in classification problems in numerous studies. …”
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15
Improved voting technique for ensemble of MLP system applied on various classification data / Saodah Omar, Iza Sazanita Isa and Junita Mohd Saleh.
Published 2010“…An Artificial Neural Network (ANN) system has been extensively applied to numerous data classification problems such as cloud classification, business applications (sales forecasting), and medical domain for clinical diagnosis. …”
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Research Reports -
16
A direct ensemble classifier for imbalanced multiclass learning
Published 2012“…Researchers have shown that although traditional direct classifier algorithm can be easily applied to multiclass classification, the performance of a single classifier is decreased with the existence of imbalance data in multiclass classification tasks.Thus, ensemble of classifiers has emerged as one of the hot topics in multiclass classification tasks for imbalance problem for data mining and machine learning domain.Ensemble learning is an effective technique that has increasingly been adopted to combine multiple learning algorithms to improve overall prediction accuraciesand may outperform any single sophisticated classifiers.In this paper, an ensemble learner called a Direct Ensemble Classifier for Imbalanced Multiclass Learning (DECIML) that combines simple nearest neighbour and Naive Bayes algorithms is proposed. …”
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Conference or Workshop Item -
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Predicting Student Performance in Object Oriented Programming Using Decision Tree : A Case at Kolej Poly-Tech Mara, Kuantan
Published 2013“…The first experiment was to test the clean dataset with seven classification techniques. Accuracy plays an important role to prove the best classification technique by using correctly classified instance as an indicator. …”
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18
Deep learning-based colorectal cancer classification using augmented and normalised gut microbiome data / Mwenge Mulenga
Published 2022“…First, to investigate the methods used to address limitations associated with microbiome-based datasets in colorectal cancer identification using deep neural network algorithms. Second, to develop novel techniques that combine the strengths of normalisation, feature engineering and data augmentation to address the problem of dimensionality, feature dominance and sparsity in colorectal cancer identification based on gut microbiome data, using deep neural network algorithms. …”
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19
Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi
Published 2019“…Based on the above components and circumstances, many studies have been performed on data clustering problems. Despite attempts to solve the data clustering issues, there are also many variants of modified algorithms in traditional information clustering that attempt to solve issues such as clustering algorithms based on condensation. …”
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20
Utilisation of Exponential-Based Resource Allocation and Competition in Artificial Immune Recognition System
Published 2011“…Artificial Immune Recognition System is one of the several immune inspired algorithms that can be used to perform classification, a data mining task. …”
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