Search Results - (( data implication tree algorithm ) OR ( data classification using algorithm ))

Diagnosis and recommender system for diabetes patient using decision tree / Nurul Aida Mohd Zamary by Mohd Zamary, Nurul Aida

“…The phase of this project is divided into data preprocessing, implementation of the decision tree algorithm, and evaluation of the algorithm and prototype. …”
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A review of the inter-correlation of climate change, air pollution and urban sustainability using novel machine learning algorithms and spatial information science by Balogun, A.-L., Tella, A., Baloo, L., Adebisi, N.

“…The study also revealed that machine learning algorithms such as random forest, gradient boosting machine, and classification and regression trees (CART) accurately predict air pollution hazard when integrated with spatial models. …”
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XAIRF-WFP: a novel XAI-based random forest classifier for advanced email spam detection by Bouke, Mohamed Aly, Alramli, Omar Imhemed, Abdullah, Azizol

“…Traditional machine learning algorithms such as Logistic Regression (LR), K-Nearest Neighbors (KNN), Decision Trees (DT), and Support Vector Machines (SVM) have been employed to mitigate this challenge. …”
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Laptop price prediction using decision tree algorithm / Nurnazifah Abd Mokti by Abd Mokti, Nurnazifah

“…The project involves data collection, data preparation, and the implementation of the decision tree algorithm for price prediction. …”
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Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms by Teoh, Chin Chuang

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

“…Since the 1960s, many algorithms for data classification have been proposed. …”
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Dengue classification system using clonal selection algorithm / Karimah Mohd by Mohd, Karimah

“…Some of the dengue data are used to test the dengue classification system to produce the classification accuracy. …”
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Enhancing Classification Algorithms with Metaheuristic Technique by Cokro, Nurwinto, Tri Basuki, Kurniawan, Misinem, ., Tata, Sutabri, Yesi Novaria, Kunang

“…Implementing this process uses classification algorithms such asNaïve Bayes, Support Vector Machine,and Random Forest. …”
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Classification of breast cancer disease using bagging fuzzy-id3 algorithm based on fuzzydbd by Nur Farahaina, Idris

“…Classification is a data mining technique used to classify varied data types according to a specific criterion. …”
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Attribute related methods for improvement of ID3 Algorithm in classification of data: A review by Nur Farahaina, Idris, Mohd Arfian, Ismail

“…Nevertheless, there are some limitations in ID3 algorithm that can affect the performance in the classification of data. …”
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Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition by Leong, Shi Xiang

“…Phase 1 is mainly to evaluate the performance of clustering algorithm (K-Means and FCM). Phase 2 is to study the performance of proposed integration system which using the data clustered to be used as train data for Naïve Bayes classifier. …”
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Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model by Sulaiman, Md. Nasir, Mohamed, Raihani, Mustapha, Norwati, Zainudin, Muhammad Noorazlan Shah

“…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. …”
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Development of classification algorithms of human gait by Koh, Chee Hong

“…Thus, this study aims to develop a classification algorithm that can effectively classify subjects with relatively simplified input data. …”
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Text Extraction Algorithm for Web Text Classification by Theab, Mustafa Muwafak

“…In this study, the experiment was conducted on five English educational websites. The created data sets are then classified using Naive-Bayes and C4.5 algorithms provided in WEKA application. …”
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An improve unsupervised discretization using optimization algorithms for classification problems by Mohamed, Rozlini, Samsudin, Noor Azah

“…According to the experimental findings, the suggested EB has a major effect on the accuracy, recall, and F-measure of data classification. The classification performance using EB outperforms other existing approaches for all datasets.…”
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An improve unsupervised discretization using optimization algorithms for classification problems by Mohamed, Rozlini, Samsudin, Noor Azah

“…According to the experimental findings, the suggested EB has a major effect on the accuracy, recall, and F-measure of data classification. The classification performance using EB outperforms other existing approaches for all datasets.…”
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DATA CLASSIFICATION SYSTEM WITH FUZZY NEURAL BASED APPROACH by LUONG, TRUNG TUAN

“…The project's objective is identifying the available data mining algorithms in data classification and applying new data mining algorithm to perform classification tasks. …”
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Classification of credit card holder behavior using K Nearest Neighbor algorithm / Ahmad Faris Rahimi by Rahimi, Ahmad Faris

“…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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Sentiment classification for malay newspaper using clonal selection algorithm / Nur Fitri Nabila Mohamad Nasir by Mohamad Nasir, Nur Fitri Nabila

“…The experimental results show that our method can achieve better performance in clonal selection algorithm sentiment classification and the data collected cannot be used at once in this model because training data is very time-consuming if using all the data. …”
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An experimental study of classification algorithms for crime prediction. by Iqbal, Rizwan, Azmi Murad, Masrah Azrifah, Mustapha, Aida, Panahy, Payam Hassany Shariat, Khanahmadliravi, Nasim

“…Classification is a well-known supervised learning technique in data mining. …”
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