[PDF] Top 20 Rough Set Approach in Machine Learning: A Review
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Rough Set Approach in Machine Learning: A Review
... in Rough set theory which uses the concept of reduct for feature ...[3,25,57,58,75,134]. Rough sets have been extensively used for feature ...primitive approach is to determine the core subset ... See full document
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Survey of review spam detection using machine learning techniques
... conduct review spam detection using various machine learning ...prominent machine learning techniques that have been proposed to solve the problem of review spam detection and ... See full document
24
Rough Set Approach for Generation of Classification Rules for Malaria
... of Rough Set can be used to find dependence relationship among data, evaluate the importance of attributes, discover the patterns of data, learn common decision-making rules, reduce all redundant objects ... See full document
5
Rough Set Approach for the Classification of Advertisement in the Development of Business Establishment
... data set and to derive the relevant data for desired ...of rough set theory has an important role to play for knowledge discovery in data ...from machine learning, statistics ... See full document
8
SOFTWARE CONFIGURATION MANAGEMENT PRACTICE IN MALAYSIA
... Intrusion detection plays a vital role in the security of communication. IDS must be intelligent enough to have high detection rate with the less false positive rate. The high amount of data and irrelevant, redundant ... See full document
14
Rough Set Approach to Multivariate Decision Trees Inducing
... novel rough- set-based multivariate decision trees (RSMDT) ...in rough set theory is used for selecting attributes in multivariate ...UCI Machine Learning Repository data sets ... See full document
10
Incremental Knowledge Acquisition for WSD: A Rough Set and IL based Method
... of rough set was proposed, many researchers have devoted to attribute reduction problem ...The rough set approach has already been applied in the management of many issues successfully, ... See full document
7
Volume 3, Issue 3, March 2014 Page 360
... comprehensive review on various techniques of flexible rule-based system, and a Machine Learning based soft ...criteria. Machine Learning based soft classifier for automatically ... See full document
5
A NOVEL APPROACH OF ROUGH SET ANALYSIS IN DISTRIBUTED DATA MINING
... Rough set theory is a new mathematical approach to imperfect ...fuzzy set theory proposed by Zadeh .Rough set theory proposed by Zpawlak presents still another attempt to this ... See full document
9
Advanced Machine Learning Approach: Deep Learning
... Deep learning can say a set of AI (AI) machine learning networks that can learn from unstructured or unlabeled ...Deep Learning is associated AI performing that imitates human brain ... See full document
5
Machine Learning Technique For Enhancing Classification Performance In Data Summarization Using Rough Set And Genetic Algorithm
... study, Rough Set (RS) is proposed to obtain the accuracy, effectiveness and appropriate summary ...hybrid approach of RS and GA to improve lack of the rough set to ensure of better ... See full document
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A Machine Learning Approach to Automatic Term Extraction using a Rich Feature Set
... 5 Experimental Evaluation and Results The first evaluation aimed to identify which fea- tures must be used for ATE (see Section 3). For that, we applied 2 methods that select attributes by evaluating the attribute ... See full document
8
Rough set approach for classifying student's learning style : a comparative analysis
... the approach of classification of four FS dimensions and IFS using Rough ...Sets. Rough Set is able to classify all 4 dimensions with significant ... See full document
6
Rough Set Approach to Development of a Knowledge-Based Expert System
... A Human Experts in the field apply heuristics acquired from years of learning successful techniques for particular circumstances. Their decisions are often based on intangibles, particular circumstances. Their ... See full document
5
Causal Learning via Manifold Regularization
... for learning causal structures (such as those above) are often rooted in data- generating causal ...on learning how to tell causal and non-causal ...causal learning—that of estimating edges in a ... See full document
32
An Improved Approach of Intention Discovery with Machine Learning for POMDP-based Dialogue Management
... Definition- Partially Observable Markov Decision Process (POMDP): The solution above in Error! Reference source not found., assumes that the state s is known when action is to b e taken; otherwise π(s) cannot be ... See full document
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A Machine Learning Approach to Sentence Ordering for Multidocument Summarization and Its Evaluation
... Even though these previous studies proposed different strategies to decide the sentence ordering, the appropriate way to combine these different methods to obtain more robust and coherent text remains unknown. In addition ... See full document
12
Traffic Flow Prediction using Combination of Support Vector Machine and Rough Set
... Various authors have proposed different techniques to design the traffic flow prediction model to get acceptable prediction accuracy. Artificial neural network (ANN), Moving average, Autoregressive Integrated Moving ... See full document
5
A Feature Selection Approach of Inconsistent Decision Systems in Rough Set
... attribute set of inconsistent decision system in [33] is defective ...attribute set with discernible matrix for incompatible decision system are also ... See full document
8
A Robust analysis of Cloud Computing Framework with Machine Learning Intentions for Industrial Applications
... like manner, the meaning of huge information was changed to information that can't be put away, oversaw and prepared by customary frameworks and advancements. To upgrade the specialized exactness of existing definitions, ... See full document
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