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Titlebook: Machine Learning Algorithms for Industrial Applications; Santosh Kumar Das,Shom Prasad Das,Aboul-Ella Hassa Book 2021 The Editor(s) (if ap

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A Hybrid Feature Selection Approach Based on LSI for Classification of Urdu Texton approaches along with Latent Semantic Indexing (LSI) to extract essential features of Urdu documents. The hybrid approach tested on the Support Vector Machine (SVM) classifier on Urdu “ROSHNI” dataset. The evaluated results were used to compare with the results obtained by individual filter featu
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Automated Document Categorization Model a supervised classifier on the initially categorized set. The categorized documents resulted from the previous step are used to train the supervised classifier. Naive Bayes classifier will be used as a statistical text classifier which uses word frequencies as features.
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Automated Categorization and Mining Tweets for Disaster Managementis done, next objective is to mine informations from the categorized tweet messages such as impacted locations, hardest hit areas, volunteer relief organization who are working on, whether that message is a complain, if any disease has spread etc. The result generated after classification and extrac
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Sentiment Analysis in Airline Data: Customer Rating Based Recommendation Prediction Using WEKA which recommendation is done. We have used different ML techniques to find out the overall sentiments generated by the customers on different service aspects and give the most suitable recommendation to customers. This helps customers as in travelers in decision making based on service type. We hav
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Image Inpainting for Irregular Holes Using Extreme Learning Machinere we train our model based on region surrounding the corrupted region. Each image is divided into two sections: the missing part that we try to reconstruct, and the context. The network does not require any region to be in some defined shape as it can also work on arbitrary regions. Final evaluatio
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Few Shot Learning for Medical Imaginglity of limited data. After establishing context, the recent advances in the application of few shot learning to medical imaging tasks such as classification and segmentation are explored. The results of these applications are examined with a discussion on its future scope.
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A Smart Document Converter: Conversion of Handwritten Text Document to Computerized Text Documentach, first the handwritten characters are extracted from the input image using digital image processing techniques and then these characters are recognized by using machine learning techniques. In this paper convolution recurrent neural network (CRNN) technique is used.
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Content-Based Airline Recommendation Prediction Using Machine Learning Techniquese amount of data, so it becomes difficult to manage things manually. Due to this fact, there is a need for a model that can help in the recommendation. This chapter aims at distinguishing reviews as positive or negative from the content of the online customer reviews submitted by the previous custom
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