[PDF] Top 20 ROUGH SETS APPLICATION FOR STUDENTS CLASSIFICATION BASED ON PERCEPTUAL DATA

ROUGH SETS APPLICATION FOR STUDENTS CLASSIFICATION BASED ON PERCEPTUAL DATA

... example, data table is divided in the group that deliver the similar attribute values, or showing the same concept delivering in the terms of attribute ...elementary sets or concepts, and conceive as the ... See full document

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System model of college students’ network behavior research based on rough sets

... including data acquisition function, decision table design function, decision table preprocessing function, decision table discretization function, attribute reduction function and rule extraction ...research ... See full document

7

An Exponential Kernel based Fuzzy Rough Sets Model for Feature Selection

... a data preprocessing step for pattern recognition, machine learning and data ...training data may result in significantly slowing down of the learning process and may increase the risk of the ... See full document

8

Palmprint Identification Based On Probabilistic Rough Sets

... individuals based on physiological and behavioral ...by classification to calculate degree of similarity of given palmprint ...identification based on probability of matching is used in probabilistic ... See full document

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Using rough set through for classification of image segmentation data

... of data mining decision systems in order to improve their impact and help facilitate practitioners’ ...information data sets and utilizing the data in hand for a sound prediction in the ... See full document

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Compositionality for perceptual classification

... modeling perceptual concepts in Larsson (2011) (using ”(to the) right” as a proof of concept) and Larsson (2013) (adding compositionality, ex- emplified by ”far right” and ”upper right”) and incorporating ... See full document

7

Educational Data Mining for Classification of Students based on their Performance

... The data received in the first step is ...raw data is processed and is converted into structured ...Firstly, data need to add by repository ...on data, we just need to drag and drop that ... See full document

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The Rough Method for Spatial Data Subzone Similarity Measurement

... GIS entity has some spatial relevance in real world. To- ber [1] proposed the famous geography first law “The spatial entities are always interrelated, especially, it have more obvious character for closed distance ... See full document

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RFKNN: ROUGH FUZZY KNN FOR BIG DATA CLASSIFICATION

... Although the kNN algorithm has shown outstanding performance in a wide variety of problems, it lacks the scalability to manage (very) large datasets. The kNN suffers high computational complexity. The complexity to find ... See full document

6

Feature Subset Selection using Rough Sets for High Dimensional Data

... The representation of raw data often uses many features, only some of which are relevant to the target concept. Since relevant features are often unknown in real-world problems, we must introduce many candidate ... See full document

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COMBINED METHODOLOGY of the CLASSIFICATION RULES for MEDICAL DATA - SETS

... extracted data could be used to teach students of oral medicine a number of orderly processes for dealing with patients with different problems depending on ...item sets and to generate association ... See full document

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An improved attribute reduction algorithm based on mutual information with rough sets theory

... finite sets which is called the domain space, A = { a 1 , a 2 , L , a [ ] A } is non empty finite attribute set, which is called the attribute set, V = ∪ A a , a ∈ A , V a is attribute’s domain range, f : U × A → ... See full document

6

Application Of Fuzzy Sets Theory In Students’ Performance Appraisal

... Contrarily to classic method, FIS method shown its ability to make a distinction of the performance level by taking into account the deepness of the gap observed between the components of evaluation. We can deduct that ... See full document

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MULTI LEVEL GROUP KEY MANAGEMENT TECHNIQUE FOR MULTICAST SECURITY IN MANET

... RRTAR is compared with other rough set attribute reduction methods i.e. Tabu Search (TSAR) by Hedar et al. [10], Ant Colony Optimization (AntRSAR) by Jensen and Shen [2, 9], Genetic Algorithm (GenRSAR) by Jensen ... See full document

7

Port throughput influence factors based on neighborhood rough sets: An exploratory study

... numeric data. So if we want to use the classical rough set theory to reduce the attributes (Hu, Yu & Xie, ...the data, which will inevitably bring about irreversible loss of information, and ... See full document

13

Lattice for covering rough approximations

... of rough set theory based on covering based rough set ...Lattice based on covering rough approximation and lattice for covering numbers are also ...is based on the notion ... See full document

6

Eye-tracking Data, Complex Networks and Rough Sets: an Attempt Toward Combining Them

... using rough sets. A measure based on rough sets is built over a complex network corresponding to eye-tracking ...of rough sets and the VPRSM approach are ... See full document

7

A map task view Generation strategy Based on Rough Set Theory

... increasing data in the data acquisition, storage and analysis has become a research ...the data model is more simple and weak a characteristics to meet the large data in the expansion of ... See full document

8

Applications of Rough Sets Theory in Data Preprocessing for Knowledge Discovery

... original data To evaluate the effect of the algorithm, we compute the misclassification error after and before instance ...only data discretized by rough sets and Chi-Merge ... See full document

6

Sequence Classification in Data Mining With Pattern Based Item Sets

... ABSTRACT:-Sequence classification is an essential undertaking in information ...sequence classification utilizing rules made out of intriguing examples found in a dataset of named sequences and going with ... See full document

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