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Supervised and Unsupervised Machine Learning Approaches—A Survey

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Part of the Lecture Notes in Electrical Engineering book series (LNEE,volume 947)


Machine learning task is broadly divided into supervised and unsupervised approaches. In supervised learning, output is already known and we have to train the model by giving lot of data called labeled dataset to train our model. The main goal is to predict the outcome. It includes regression and classification problem. In unsupervised learning, no output mapping with input as well as it is independent in nature. The dataset used in unsupervised machine learning is unlabeled. The main focus of this paper is to give detailed understanding of supervised and unsupervised machine learning algorithm with pseudocodes.


  • Supervised
  • Unsupervised
  • Decision tree
  • K-means
  • PCA

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Correspondence to C. Esther Varma .

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Esther Varma, C., Prasad, P.S. (2023). Supervised and Unsupervised Machine Learning Approaches—A Survey. In: Kumar, A., Senatore, S., Gunjan, V.K. (eds) ICDSMLA 2021. Lecture Notes in Electrical Engineering, vol 947. Springer, Singapore.

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-19-5935-6

  • Online ISBN: 978-981-19-5936-3

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