Search Results - (( learning classification problems algorithm ) OR ( evolution classification mining algorithm ))
Search alternatives:
- evolution classification »
- classification mining »
- mining algorithm »
- problems »
-
1
Class binarization with self-adaptive algorithm to improve human activity recognition
Published 2018“…However, the learning complexity of classification is increased due to the expansion number of learning model. …”
Get full text
Get full text
Thesis -
2
Classification of Immunosignature Using Random Forests for Cancer Diagnosis
Published 2015“…To attain this essential research purpose, a minimum set of genes that can assure higher performance in classification using data mining algorithms need to be detected. …”
Get full text
Get full text
Get full text
Proceeding Paper -
3
Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets
Published 2019“…The proposed algorithm is grounded on the two famous metaheuristic algorithms: cuckoo search (CS) and covariance matrix adaptation evolution strategy (CMA-es). …”
Get full text
Get full text
Thesis -
4
Classification with degree of importance of attributes for stock market data mining
Published 2004“…The SVM is a training algorithm for learning classification and regression rules from data [7]. …”
Get full text
Get full text
Article -
5
Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition
Published 2017“…The problems in applying unsupervised learning/clustering is that this method requires teacher during the classification process and it has to learn independently which may lead to poor classification. …”
Get full text
Get full text
Thesis -
6
Accelerating learning performance of back propagation algorithm by using adaptive gain together with adaptive momentum and adaptive learning rate on classification problems
Published 2011“…The back propagation (BP) algorithm is a very popular learning approach in feedforward multilayer perceptron networks. …”
Get full text
Get full text
Get full text
Article -
7
Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model
Published 2018“…Meanwhile, Kmeans clustering algorithm has also been reported has widely known for solving most unsupervised classification problems. …”
Get full text
Get full text
Get full text
Article -
8
Grid-Based Classifier as a Replacement for Multiclass Classifier in a Supervised Non-Parametric Approach
Published 2009“…This method carries the advantages of the two previous methods in order to improve the classification tasks. The problem with the current lazy algorithms is that they learn quickly, but classify very slowly. …”
Get full text
Get full text
Thesis -
9
Classification model for water quality using machine learning techniques
Published 2015“…This article proposes a suitable classification model for classifying water quality based on the machine learning algorithms. …”
Get full text
Get full text
Article -
10
Grid base classifier in comparison to nonparametric methods in multiclass classification
Published 2010“…This method carries the advantages of the two previous methods in order to improve the classification tasks. The problem with the current lazy algorithms is that they learn quickly, but classify very slowly. …”
Get full text
Get full text
Get full text
Article -
11
A Hybrid of Ant Colony Optimization Algorithm and Simulated Annealing for Classification Rules
Published 2013“…The successful work on hybridization of ACO and SA algorithms has led to the improved learning ability of ACO for classification. …”
Get full text
Get full text
Get full text
Get full text
Thesis -
12
Y-type Random 2-satisfiability In Discrete Hopfield Neural Network
Published 2024“…Additionally, the proposed Hybrid Differential Evolution Algorithm was implemented into the training phase to ensure that the cost function of the Discrete Hopfield Neural Network is minimized. …”
Get full text
Get full text
Thesis -
13
A Comparison Between Levenberg-Marquardt (LM) Intelligent System And Bayesian Regularization (BR) Intelligent System For Flow Regime Classification
Published 2006“…The purpose of this project is to study the performance, leaning time and, output of Levenberg-Marquardt (LM) intelligent system and Bayesian Regularization (BR) intelligent system through a classification problem. These studies will help in choosing the right training algorithm for classification problem involved. …”
Get full text
Get full text
Monograph -
14
Case Slicing Technique for Feature Selection
Published 2004“…One of the problems addressed by machine learning is data classification. …”
Get full text
Get full text
Thesis -
15
An improve unsupervised discretization using optimization algorithms for classification problems
Published 2024“…This paper addresses the classification problem in machine learning focusing on predicting class labels for datasets with continuous features. …”
Get full text
Get full text
Get full text
Article -
16
An improve unsupervised discretization using optimization algorithms for classification problems
Published 2024“…This paper addresses the classification problem in machine learning, focusing on predicting class labels for datasets with continuous features. …”
Get full text
Get full text
Get full text
Article -
17
Autism Spectrum Disorder Classification Using Deep Learning
Published 2021“…The goal of this paper is to evaluate the deep learning algorithm for people placed in the Autism Spectrum Disorder (ASD) classification. …”
Get full text
Get full text
Get full text
Get full text
Article -
18
Classification of breast cancer disease using bagging fuzzy-id3 algorithm based on fuzzydbd
Published 2022“…One of the most powerful machine learning methods to handle classification problems is the decision tree. …”
Get full text
Get full text
Thesis -
19
Automatic email classification system / Phang Siew Ting
Published 2003“…For this purpose, several Machine Learning algorithms has been purposed to automate the classification of emails. …”
Get full text
Get full text
Thesis -
20
Waste management using machine learning and deep learning algorithms
Published 2020“…So, we are proposing an automated waste classification problem utilizing Machine Learning and Deep Learning algorithms. …”
Get full text
Get full text
Get full text
Get full text
Article