Search Results - (( java implementation bat algorithm ) OR ( program program bayes algorithm ))

Fuzzy modeling using Bat Algorithm optimization for classification by Noor Amidah, Ahmad Sultan

“…A Sazonov Engine which is a fuzzy java engine is use to apply Bat Algorithm in the experiment. …”
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Airline flight delay prediction using Naïve Bayes algorithm / Ahmad Adib Baihaqi Shukri by Shukri, Ahmad Adib Baihaqi

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Classification Algorithms to Determine Students’ Specialization in a Higher Education Institution by Tri Basuki, Kurniawan, Indah, Hidayanti

“…After that, we looked at how Python programming classification algorithms like Support Vector Machine (SVM), Naïve Bayes, Random Forest, and Decision Tree performed in classifying the areas of specialization of the students. …”
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Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization by Mohammad Ata, Karimeh Ibrahim

“…In this system, the layout was designed under two categories which are the standard bay size and the small bay size to increase the parking bays. …”
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Sentiment mining in twitter for early depression detection / Najihah Salsabila Ishak by Ishak, Najihah Salsabila

“…A classifier model is developed using Naive Bayes characteristics. A comparison between built-in Scikit Learn Naive Bayes algorithm, and the scratch Naive Bayes algorithm is used to measure its effectiveness in terms of accuracy. …”
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Divorce prediction using Naive Bayes / Alia Hannani Ahmad Bakri by Ahmad Bakri, Alia Hannani

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Novice programmers’ emotion and competency assessments using machine learning on physiological data / Fatima Jannat by Fatima, Jannat

“…This work investigates the suitability and effectiveness of machine learning algorithms such as Multinomial Naive Bayes, KNN, Logistic Regression, Decision Tree for predicting levels of arousal intensity among the programmers and LSTM deep learning algorithm to classify the programmers according to their performance. …”
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Evaluation of data mining classification and clustering techniques for diabetes / Tuba Pala and Ali Yilmaz Camurcu by Pala, Tuba, Camurcu, Ali Yilmaz

“…Multilayer Perceptron algorithm has been the best algorithm with the highest success percentage in both of the programs; Decision Trees has been the algorithm which has the lowest success percentage again in both of the programs. …”
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Sentiment Analysis of Airline Reviews Using Naive Bayes Algorithm / Ahmad Firdaus Maliki by Maliki, Ahmad Firdaus

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Employability prediction based on personality test using Naive Bayes Algorithm / Mohd Alief Mukhlis Mohd Adnin by Mohd Adnin, Mohd Alief Mukhlis

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Car recognition using Bayes Classifier / Nur Atiqah Mat Samadi by Mat Samadi, Nur Atiqah

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Classification and visualization on eligibility rate of applicant’s LinkedIn account using Naïve Bayes / Nurul Atirah Ahmad, Khyrina Airin Fariza Abu Samah and Nuwairah Aimi Ahmad... by Ahmad, Nurul Atirah, Abu Samah, Khyrina Airin Fariza, Ahmad Kushairi, Nuwairah Aimi

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Case Slicing Technique for Feature Selection by A. Shiba, Omar A.

“…CST was compared to other selected classification methods based on feature subset selection such as Induction of Decision Tree Algorithm (ID3), Base Learning Algorithm K-Nearest Nighbour Algorithm (k-NN) and NaYve Bay~sA lgorithm (NB). …”
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Cyber fraud profiling with routine activity theory using data mining techniques / Sunardi, Abdul Fadlil and Nur Makkie Perdana Kusuma by -, Sunardi, -, Abdul Fadlil, Perdana Kusuma, Nur Makkie

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Twitter sentiment analysis of Malaysian fast food restaurant chains: a novel approach to understand customer perception using Naïve Bayes / Muhammad Hafeez Hakimi Muhd Zahidi Ridzu... by Muhd Zahidi Ridzuan, Muhammad Hafeez Hakimi, Abd Halim, hairul Nizam

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Mobile app of mood prediction based on menstrual cycle using machine learning algorithm / Nur Hazirah Amir by Amir, Nur Hazirah

“…It implemented Supervised Learning algorithm with Bayes’ Theorem model for the calculation of mood prediction using Python programming language. …”
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Towards a better feature subset selection approach by Shiba, Omar A. A.

“…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.…”
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Prediction of stroke disease using machine learning techniques / Syarifah Adilah Mohamed Yusoff ... [et al.] by Mohamed Yusoff, Syarifah Adilah, Warris, Saiful Nizam, Abu Bakar, Mohd Saifulnizam, Kadar, Rozita

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SpickME: Choosing spectacles prediction system by using multinomial Naïve Bayes / Nurul Nabilah Johari by Johari, Nurul Nabilah

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Development of an intelligent information system for financial analysis depend on supervised machine learning algorithms by Lei, X., Mohamad, U.H., Sarlan, A., Shutaywi, M., Daradkeh, Y.I., Mohammed, H.O.

“…ML can examine millions of data sets in a short period of time without being explicitly programmed to improve the results. This type of algorithm can aid financial institutions in making grant selections for their clients. …”
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