Search Results - (( data classification (problems OR problem) algorithm ) OR ( using function machine algorithm ))
Search alternatives:
- data classification »
- machine algorithm »
- using function »
-
1
A Hybrid of Ant Colony Optimization Algorithm and Simulated Annealing for Classification Rules
Published 2013“…Benchmark data sets from various fields were used to test the proposed algorithms. …”
Get full text
Get full text
Get full text
Get full text
Thesis -
2
A hybrid approach for artificial immune recognition system / Mahmoud Reza Saybani
Published 2016“…Many researchers, who have developed methods and algorithms within the field of artificial intelligence, machine learning and data mining, have addressed extracting useful information from the data. …”
Get full text
Get full text
Thesis -
3
Support directional shifting vector: A direction based machine learning classifier
Published 2021“…The positional error of the linear function has been modelled as a loss function which is iteratively optimized using the gradient descent algorithm. …”
Get full text
Get full text
Get full text
Article -
4
A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem
Published 2016“…There are two methods in dealing with imbalanced classification problem, which are based on data or algorithmic level. …”
Get full text
Get full text
Get full text
Thesis -
5
Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model
Published 2018“…Expectation maximization (EM) is one of the representatives clustering algorithms which have broadly applied in solving classification problems by improving the density of data using the probability density function. …”
Get full text
Get full text
Get full text
Article -
6
Enhancement of new smooth support vector machines for classification problems
Published 2011“…Research on Smooth Support Vector Machine (SSVM) for classification problem is an active field in data mining. …”
Get full text
Get full text
Thesis -
7
Logistic regression methods for classification of imbalanced data sets
Published 2012“…Classification of imbalanced data sets is one of the important researches in Data Mining community, since the data sets in many real-world problems mostly are imbalanced class distribution. …”
Get full text
Get full text
Thesis -
8
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. …”
Get full text
Get full text
Get full text
Article -
9
An improvement of back propagation algorithm using halley third order optimisation method for classification problems
Published 2020“…While H-DFP, the highest improvement achieved in generalisation accuracy is on the Seeds classification with 41.73% improvement for 70:30 data division. …”
Get full text
Get full text
Get full text
Get full text
Thesis -
10
Jogging activity recognition using k-NN algorithm
Published 2022“…The k-NN algorithm is a simple and easy-to-implement supervised machine learning algorithm that can be used to solve both classification and regression problems. …”
Get full text
Get full text
Get full text
Academic Exercise -
11
Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy
Published 2019“…The proposed algorithm is compared with the state-of-the-art feature selection algorithms using three different datasets. …”
Get full text
Get full text
Get full text
Thesis -
12
Hand gesture recognition for autism diagnosis using Support Vector Machine (SVM) Algorithm / Muhammad Asyraf Mohamad Zain
Published 2020“…To counter this problem, a system has been proposed to detect the hand gesture using one of the machine learning technique which is Support Vector Machine (SVM) Algorithm. …”
Get full text
Get full text
Thesis -
13
Computational Technique for an Efficient Classification of Protein Sequences With Distance-Based Sequence Encoding Algorithm
Published 2017“…Machine learning is being implemented in bioinformatics and computational biology to solve challenging problems emerged in the analysis and modeling of biological data such as DNA, RNA, and protein. …”
Get full text
Get full text
Article -
14
New Instances Classification Framework On Quran Ontology Applied To Question Answering System
Published 2019“…The existing classification approach used machine learning: Backpropagation Neural Network. …”
Get full text
Get full text
Get full text
Article -
15
-
16
Investigation of features for classification RFID reading between two RFID reader in various support vector machine kernel function
Published 2022“…The Polynomial-SVM model is capable of delivering a classification accuracy of 84.81 and 20.00% of the error rate in test data by using the function MIN extracted. …”
Get full text
Get full text
Get full text
Get full text
Conference or Workshop Item -
17
Predicting noise-induced hearing loss (NIHL) in TNB workers using GDAM algorithm
Published 2012“…The traditional Back-propagation Neural Network (BPNN) is a supervised Artificial Neural Networks (ANN) algorithm. It is widely used in solving many real time problems in world. …”
Get full text
Get full text
Get full text
Get full text
Thesis -
18
Named entity recognition using a new fuzzy support vector machine.
Published 2008“…In our method we have employed Support Vector Machine as one of the best machine learning algorithm for classification and we contribute a new fuzzy membership function thus removing the Support Vector Machine’s weakness points in NER precision and multi classification. …”
Get full text
Get full text
Article -
19
On equivalence of FIS and ELM for interpretable rule-based knowledge representation
Published 2023Article -
20
Rough Neural Networks Architecture For Improving Generalization In Pattern Recognition
Published 2004“…The network stages are a feature extraction network, and a classification network. The extraction network is composed of rough neurons that accounts for the upper and lower approximations and embeds a membership function to replace ordinary activation functions. …”
Get full text
Get full text
Thesis
