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Later, we chose an appropriate strategy (learning algorithm) for an effcient model training. Our empirical evaluation and experimental analysis show that the proposed method performs better compared with other variable selection-based dimension reduction and further text categorisation methods. We exploited several systematic and careful experimentation scenarios in this work to discover what architecture works best for this BBC news dataset. We used 3 hidden layers, each layer with 128 neurons. We observed this architecture optimal as per our specific problem experimentation. Moreover, our proposed method can be useful for improving efficiency and speed-up the calculations on certain datasets. <\/jats:p>","DOI":"10.1142\/s0219649222500277","type":"journal-article","created":{"date-parts":[[2022,5,9]],"date-time":"2022-05-09T16:14:21Z","timestamp":1652112861000},"source":"Crossref","is-referenced-by-count":1,"title":["Statistically Empirical Integrated Approach for Knowledge Refined Text Classification"],"prefix":"10.1142","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9831-0223","authenticated-orcid":false,"given":"N.\u00a0Venkata","family":"Sailaja","sequence":"first","affiliation":[{"name":"Department of Computer Science and Engineering, VNR Vignana Jyothi Institute of Engineering and Technology, Hyderabad 500090, Telangana, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"L.\u00a0Padma","family":"Sree","sequence":"additional","affiliation":[{"name":"Department of Electronics and Communication Engineering, VNR Vignana Jyothi Institute of Engineering and Technology, Hyderabad 500090, Telangana, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"N.","family":"Mangathayaru","sequence":"additional","affiliation":[{"name":"Department of Information Technology, VNR Vignana Jyothi Institute of Engineering and Technology, Hyderabad 500090, Telangana, India"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"219","published-online":{"date-parts":[[2022,5,7]]},"reference":[{"key":"S0219649222500277BIB001","doi-asserted-by":"publisher","DOI":"10.1016\/S0004-3702(97)00063-5"},{"key":"S0219649222500277BIB002","first-page":"5462","volume":"9","author":"Chakriswaran P","year":"2019","journal-title":"Future Research Directions, and Open Issues. 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