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Feature Subset Selection Using Meta Heuristic Approaches

Thesis Info

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Author

Khan, Ayesha

Program

PhD

Institute

National University of Computer and Emerging Sciences

City

Islamabad

Province

Islamabad

Country

Pakistan

Thesis Completing Year

2019

Thesis Completion Status

Completed

Subject

Computer Science

Language

English

Link

http://prr.hec.gov.pk/jspui/bitstream/123456789/10740/1/Ayesha%20Khan_CS_2019_FAST%20NU.pdf

Added

2021-02-17 19:49:13

Modified

2024-03-24 20:25:49

ARI ID

1676727758410

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The expansion of the data is so rapid in the real world today that, now accumulating and processing it is a huge task. This growth is exponential and when Data Mining (DM) tools are applied to analyze this enormous data, it makes the algorithms time-consuming and expensive. One of the most important algorithm in DM for analyzing the data is the tool for classi cation. Classi cation is a function of DM for predicting the class of a sample by building a classi er or a prediction model on the basis of already collected samples with their class. The dataset used for classi cation is a supervised data with di erent features or attribute. During classi cation some features can be of great signi cance while some could be irrelevant and redundant. The learning and prediction time of classi cation algorithms is reduced using feature selection. This decrease in time is due to the time saved on the cost of features that are not selected through feature selection. Feature selection also provides understanding into the nature of the problem to be solved. So, there is a vital need of removing those irrelevant and redundant features before building a classi er. This research is based on solving the problem of feature subset selection (FSS) that chooses the features/attributes that are of signi cant value for the classi er to be built. These signi cant features would reduce the data that will eventually help to improve the accuracy and reliability of big data analytics. The reduction of data eventually would increase the accuracy and reliability of decision support systemsespeciallycriticalhealthrelateddecisionsupportsystems. Other areas include sentiment analysis, opinion mining, drug discovery, tumor detection, stroke detection and many other such applications. Therst phase of this research has the novelty of considering FSS prob lem as multi-objective problem and solving it using two metaheuris tic techniques that are Non-dominating Sorting Genetic Algorithm II (NSGA-II) and Multi-objective Particle Swarm Optimization altered to solve FSS as a binary problem (BMOPSO). The experimentation results represent the importance of considering FSS as multi-objective problem as it outperforms against current techniques of FSS not only in terms of the accuracy of a classi er but number features reduced. The sec ond phase of this research explores Ant Colony Optimization (ACO) technique for FSS which is another meta-heuristic technique. To fur ther re ne the search, the signi cance of each feature is measured using minimum Redundancy Maximum Relevance (mRMR) technique before applying ACO. The results show that proposed technique performs bet ter when compared with other existing biological inspired algorithms for FSS. Both of the phases of this research use di erent real world datasets taken from UCI machine repository and k-fold cross validation is used to further authenticate the results of the proposed techniques. The fea ture subset selection primarily deals with the data representation for the classi cation process and reduces the computational complexity and prediction accuracy.
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Muhammad’s (Saw) Treatment of the Jewish Tribes: A Critique of Robert Spencer’s Views

It is incontrovertibly true that Islam advocates peaceful coexistence with the adherents of other creeds. The holy Qur’an, the primary source of Islamic Shari‘ah, vividly recommends freedom of conscience and religion. Similarly, the prophet (SAW), being the perfect role model for the entire humanity, preached and practiced the lofty ideals propounded by the holy Qur’an and peacefully coexisted with the followers of Judaism and Christianity. Furthermore, the four rightly guided caliphs exhibited tolerant attitude towards their Jews and Christian subjects. In the presence of these models, nonetheless, many contemporary critics of Islam are disinclined to admit this explicit reality. Robert Spencer also sees eye to eye with them. Robert Spencer is an American author and he has published twelve books. He is a member of Melkite Greek Catholic Church. He looks on Islam as a highly intolerant religion. In this connection, he singles out Muhammad’s (SAW) treatment of various Jewish tribes. He maintains that all Jewish tribes viz. Banu Na╔hir, Banu Qaiʽn┴q┐ʽ and Banu Qurai╔ah “received the wrath of Muhammad”. This brief study aims to prove that the treatment meted out to the Jews was not founded on religious prejudice and malice; it was rather commensurate with their wicked demeanor.

Nutritional Assessment of Some Neglected and Underutilized Vegetables Wildly Grown in Sindh

comparison of nutritional value of nontraditional with commercial vegetables in Sindh. The questionnaire survey methodology was used to collect the data on the utilization and consumption of nontraditional and commercial vegetables in Mirpurkhas of Sindh province, Pakistan in 2014. On the basis of survey spinach, horse radish tree flowers, lambs quarter and gram leaves were collected in January, 2014 whereas, amaranthus was collected in the months of July-August, 2014 from district Mirpurkhas, packed with proper labelling and brought to the Institute of Food Sciences and Technology, Sindh Agriculture University Tandojam for processing and nutritional analysis. The edible parts of vegetables were washed and divided into five sets namely control, boiled, cooked, thermally dehydrated and shade dried. The data of survey showed that gram leaves was the most popular nontraditional vegetable eaten frequent or occasionally by 82% respondents only 18% respondents never tasted or do not know this vegetable. Next vegetables which majority of respondent never tasted or did not know included amaranthus and lambs quarter. About 62% respondents never tasted or do not know horse radish tree flowers as vegetable while 38% respondents answered they eat occasionally. The nontraditional (lambs quarter, horse radish tree flowers, gram leaves, amaranthus) and commercial (spinach) vegetables were analyzed for their nutritive, mineral, vitamin, phytochemical and chlorophyll composition. The highest moisture content (92.66%) was found in spinach under boiled method followed by 88.760% moisture content in the same vegetable at fresh (control). Maximum ash content (16.15%) in horse radish tree flowers followed by 10.56% ash content in amaranthus under thermally dehydration. Protein content was found greater (7.56%) in gram leaves under thermal dehydration method. However, minimum protein of 1.04% was found in spinach under boiling method. The maximum value of 3.85% in horse radish tree flowers under cooking method while minimum fat content i.e. 0.85 and 0.75% was found in spinach and lambs quarter, respectively at boiling method. The highest value (13.35%) of fiber was obtained in thermally dried sample of horse radish tree flowers whereas the lowest value was recorded in boiled sample of spinach. However, higher carbohydrate (68.62%) content was found in lambs quarter at shade drying. The nontraditional vegetables also contain organic acids (e.g. lactic acid, citric acid, acetic acid, tartaric acid) in all the selected vegetables. The nontraditional and commercial vegetables were also recorded with significant amount of vitamins and phytochemicals. The energy value was found lowest in fresh spinach (38.35 Kcal 100g-1) hence was also detected lowered in other processing methods as compared to nontraditional vegetables. The results of the sensory evaluation of the uncooked and cooked samples in present study revealed that in uncooked samples, horse radish tree flowers obtained highest scores in appearance, color, odor, texture, taste, overall acceptability and purchase i.e. 4.90, 4.70, 4.00, 3.90, 3.50, 3.80 and 3.80. While in traditionally cooked samples lambs quarter and gram leaves retained original color and thus obtained the highest scores in appearance and taste i.e. 3.70, 3.90 and 3.70, 3.50, respectively. Acceptability study by hedonic scoring showed that nontraditional vegetables (horse radish tree flowers, lambs quarter, and gram leaves and amaranthus) made by traditional cooking were most acceptable as compared with commercial vegetable (spinach). These nontraditional vegetables when consumed in cooked form could also be a good source of nutrients. Principal component analysis revealed that the first seven principal components explained about 94.79% of the total variability in the observed parameters. Moisture, total solid, ash, fiber, carbohydrate, nitrogen free extract, energy value, acetic acid, citric acid, oxalic acid, tartaric acid, copper, iron, zinc, manganese, calcium, sodium and potassium resulted the most effective variables for the first principal component. Saponins, flavinoids, phenol and vitamin B3 were major contributors to second principal component, while tannins content was useful to define the third principal component. It was concluded that the nutrient and bioactive contents obtained from selected vegetables seem to suggest that the vegetables have high potential to contribute to the nutritional and health status of local as well as urban communities in Sindh Pakistan. Their use in the communities should therefore, be promoted. Taking into account the amount of nutrient and bioactive content in the selected nontraditional vegetable, these plants could be valuable and important contributor to the diets of the people in Sindh, Pakistan.