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The survey reveals that feature selection is the most time consuming and niche skill demanding part of the entire workflow. This paper shows how feature selection is successfully automated without sacrificing the decision making accuracy and thereby reducing the project completion time and cost of hiring expensive resources. Several pattern recognition principles and state of art (SoA) ML techniques are followed to design the overall approach for the proposed automation. Three data sets are considered to establish the proof-of-concept. Experimental results show that the proposed automation is able to reduce the time for feature selection to 2 days instead of 4 -- 6 months which would have been required in absence of the automation. This reduction in time is achieved without any sacrifice in the accuracy of the decision making process. Proposed method is also compared against Multi Layer Perceptron (MLP) model as most of the state of the art works on IoTA uses MLP based Deep Learning. Moreover the feature selection method is compared against SoA feature reduction technique namely Principal Component Analysis (PCA) and its variants. The results obtained show that the proposed method is effective.<\/jats:p>","DOI":"10.1145\/3231535.3231538","type":"journal-article","created":{"date-parts":[[2018,6,7]],"date-time":"2018-06-07T13:57:43Z","timestamp":1528379863000},"page":"24-30","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":14,"title":["Automation of feature engineering for IoT analytics"],"prefix":"10.1145","volume":"15","author":[{"given":"Snehasis","family":"Banerjee","sequence":"first","affiliation":[{"name":"TCS Research &amp; Innovation, Kolkata, West Bengal"}]},{"given":"Tanushyam","family":"Chattopadhyay","sequence":"additional","affiliation":[{"name":"TCS Research &amp; Innovation, Kolkata, West Bengal"}]},{"given":"Arpan","family":"Pal","sequence":"additional","affiliation":[{"name":"TCS Research &amp; Innovation, Kolkata, West Bengal"}]},{"given":"Utpal","family":"Garain","sequence":"additional","affiliation":[{"name":"Indian Statistical Institute, Kolkata, West Bengal"}]}],"member":"320","published-online":{"date-parts":[[2018,6,5]]},"reference":[{"key":"e_1_2_1_1_1","volume-title":"Yoshua Bengio and Aaron Courville Deep Learning","author":"Ian Goodfellow","year":"2016","unstructured":"Ian Goodfellow , Yoshua Bengio and Aaron Courville Deep Learning , MIT Press , 2016 . 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