Search Results - (( model evaluation a algorithm ) OR ( early identification mining algorithm ))

Outlier Detection Technique in Data Mining: A Research Perspective by Mansur, M. O., Md. Sap, Mohd. Noor

“…Finding ,removing and detecting outliers is very important in data mining, for example error in large databases can be extremely common, so an important property of a data mining algorithm is robustness with respect to outliers in the database. …”
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Machine-learning approach using thermal and synthetic aperture radar data for classification of oil palm trees with basal stem rot disease by Che Hashim, Izrahayu

“…The main benefit of this study is the development of an appropriate model for early identification and severity classification of BSR disease in oil palms via remote sensing and data mining approaches rapidly and cost-effectively.…”
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Performances analysis of heart disease dataset using different data mining classifications by Wan Zunaidi, Wan Hajarul Asikin, Saedudin, RD Rohmat, Ali Shah, Zuraini, Kasim, Shahreen, Sen, Seah Choon, Abdurohman, Maman

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A Machine Learning Classification Application to Identify Inefficient Novice Programmers by Khan I., Al-Mamari A., Al-Abdulsalam B., Al-Abdulsalam F., Al-Khansuri M., Iqbal Malik S., Ahmad A.R.

Sentiment-analysis to detect early depressive symptom in Bangla language from social media: a review study by Hassan, Md. Hasibul, Kamaruddin, Azrina, Azmi Murad, Masrah Azrifah

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Polycystic Ovary Syndrome (PCOS) prediction system using PSO-SVM / Lukman Hakim Shaufee, Hamidah Jantan and Ummu Fatihah Mohd Bahrin by Shaufee, Lukman Hakim

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Evaluation of MLP-ANN Training Algorithms for Modeling Soil Pore-Water Pressure Responses to Rainfall by Mustafa, M.R., Rezaur, R.B., Saiedi, Saied, Rahardjo, H., Isa, M.H.

“…The performance of the training algorithms was evaluated using standard performance evaluation measures—root mean square error, coefficient of efficiency, and the time and number of epochs required to reach a predefined accuracy. …”
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Neural Networks Ensemble: Evaluation of Aggregation Algorithms for Forecasting by HASSAN, SAIMA

“…The aggregation algorithms were employed on the forecasts obtained from all individual NN models as well as on a number of the best forecasts obtained from the best NN models. …”
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Diagnosis and recommender system for diabetes patient using decision tree / Nurul Aida Mohd Zamary by Mohd Zamary, Nurul Aida

“…This project aims to develop a decision-making support model for diabetes diagnosis and treatment recommendation using the decision tree algorithm. …”
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A Model for Evaluation of Cryptography Algorithm on UUM Portal by Norliana, Abdul Majid

“…The purpose of this project are to construct and provide guidelines to develop a simulation model to evaluate cryptography algorithm in terms of encryption speed and descryption speed on UUM portal. …”
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Neural network ensemble: Evaluation of aggregation algorithms in electricity demand forecasting by Hassan, S., Khosravi, A., Jaafar, J.

“…These algorithms include equal-weights combination of Best NN models, combination of trimmed forecasts, and Bayesian Model Averaging (BMA). …”
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Neural network ensemble: Evaluation of aggregation algorithms in electricity demand forecasting by Hassan, S., Khosravi, A., Jaafar, J.

“…These algorithms include equal-weights combination of Best NN models, combination of trimmed forecasts, and Bayesian Model Averaging (BMA). …”
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Neural network ensemble: Evaluation of aggregation algorithms in electricity demand forecasting by Hassan, S., Khosravi, A., Jaafar, J.

“…These algorithms include equal-weights combination of Best NN models, combination of trimmed forecasts, and Bayesian Model Averaging (BMA). …”
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Unifying the evaluation criteria of many objectives optimization using fuzzy Delphi method by Mohammed, Rawia Tahrir, Yaakob, Razali, Mohd Sharef, Nurfadhlina, Abdullah, Rusli

“…This study proposed a distinct unifying model for the MaOO evaluation criteria using the fuzzy Delphi method. …”
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Evaluation of different peak models of eye blink EEG for signal peak detection using artificial neural network by Adam, A., Ibrahim, Z., Mokhtar, N., Shapiai, M.I., Mubin, M.

“…This study evaluates the performance of eye blink EEG signal peak detection algorithm for four different peak models which are Dumpala's, Acir's, Liu's, and Dingle's peak models. …”
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Evaluation of the Transfer Learning Models in Wafer Defects Classification by Jessnor Arif, Mat Jizat, Anwar, P. P. Abdul Majeed, Ahmad Fakhri, Ab. Nasir, Zahari, Taha, Yuen, Edmund, Lim, Shi Xuen

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Analytical Study Of Machine Learning Models For Stock Trading In Malaysian Market by Hazirah Halul

“…Previous studies usually concentrate on the forecasting stock index or selecting a few stocks with restricted features. Therefore, this study focused to contribute on evaluating different algorithm models such as traditional ML and deep learning models with big stock data of multiple parameters from selected companies in Bursa Malaysia. …”

Multistep forecasting for highly volatile data using new algorithm of Box-Jenkins and GARCH by Siti Roslindar, Yaziz, Roslinazairimah, Zakaria

“…Based on the empirical results, the proposed algorithm of multistep ahead forecast to the algorithm of BJ-G provides a promising procedure to assess the performance of the BJ-G model in forecasting a highly volatile time series data. …”
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Performance evaluation and benchmarking of an extended computational model of ant colony system for DNA sequence design by Zuwairie, Ibrahim, Mohd Falfazli, Mat Jusof, Mohd Zaidi, Mohd Tumari

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Dynamic Bayesian networks and variable length genetic algorithm for designing cue-based model for dialogue act recognition by Yahya, Anwar Ali, Mahmod, Ramlan, Ramli, Abd Rahman

“…The model is, essentially, a dynamic Bayesian network induced from manually annotated dialogue corpus via dynamic Bayesian machine learning algorithms. …”
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