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1

Albalate, Amparo, and Wolfgang Minker. Semi-Supervised and Unsupervised Machine Learning. John Wiley & Sons, Inc., 2013. http://dx.doi.org/10.1002/9781118557693.

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2

Baruque, Bruno. Fusion methods for unsupervised learning ensembles. Springer, 2010.

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3

H, Fisher Douglas, Pazzani Michael John 1958-, and Langley Pat, eds. Concept formation: Knowledge and experience in unsupervised learning. Morgan Kaufmann Publishers, 1991.

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4

Aldrich, Chris, and Lidia Auret. Unsupervised Process Monitoring and Fault Diagnosis with Machine Learning Methods. Springer London, 2013. http://dx.doi.org/10.1007/978-1-4471-5185-2.

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5

Aldrich, Chris. Unsupervised Process Monitoring and Fault Diagnosis with Machine Learning Methods. Springer London, 2013.

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6

Celebi, M. Emre, and Kemal Aydin. Unsupervised Learning Algorithms. Springer London, Limited, 2016.

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7

Unsupervised Learning Algorithms. Springer, 2016.

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8

Bakshi, Elisabeth. Unsupervised Learning : Identify Machine Learning Tasks: Machine Learning Course. Independently Published, 2021.

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9

Unsupervised Learning with R. Packt Publishing, Limited, 2015.

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10

Unsupervised Learning with R. Packt Publishing, 2015.

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11

Jo, Taeho. Machine Learning Foundations: Supervised, Unsupervised, and Advanced Learning. Springer International Publishing AG, 2022.

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12

Jo, Taeho. Machine Learning Foundations: Supervised, Unsupervised, and Advanced Learning. Springer International Publishing AG, 2021.

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13

Lopez, César Perez. Machine Learning with Matlab. Unsupervised Learning Techniques: Classification. Lulu Press, Inc., 2020.

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14

Perez, C. Machine Learning Techniques: UNSUPERVISED LEARNING. EXAMPLES with MATLAB. Independently Published, 2019.

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15

Muneesawang, Paisarn, Ling Guan, Matthew Kyan, and Kambiz Jarrah. Unsupervised Learning: A Dynamic Approach. Wiley & Sons, Incorporated, John, 2014.

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16

Muneesawang, Paisarn, Ling Guan, Matthew Kyan, and Kambiz Jarrah. Unsupervised Learning: A Dynamic Approach. Wiley & Sons, Incorporated, John, 2014.

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17

Perez, C. Segmentation with Matlab. Unsupervised Machine Learning Techniques. Independently Published, 2019.

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18

Colins, Michael. Machine Learning: An Introduction To Supervised & Unsupervised Learning Algorithms. Createspace Independent Publishing Platform, 2017.

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19

Sage, Anderson. Machine Learning Foundation: An Introduction to Supervised and Unsupervised Learning. Independently Published, 2022.

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20

Unsupervised and Transfer Learning: Challenges in Machine Learning, Volume 7. Microtome Publishing, 2013.

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21

Baruque, Bruno. Fusion Methods for Unsupervised Learning Ensembles. Springer, 2010.

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22

Baruque, Bruno. Fusion Methods for Unsupervised Learning Ensembles. Springer, 2014.

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23

Langley, Pat, Michael J. Pazzani, and Douglas H. Fisher. Concept Formation: Knowledge and Experience in Unsupervised Learning. Elsevier Science & Technology Books, 2014.

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24

Aldrich, Chris, and Lidia Auret. Unsupervised Process Monitoring and Fault Diagnosis with Machine Learning Methods. Springer, 2013.

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25

Waggoner, Philip D. Unsupervised Machine Learning for Clustering in Political and Social Research. Cambridge University Press, 2021.

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26

Waggoner, Philip D. Unsupervised Machine Learning for Clustering in Political and Social Research. Cambridge University Press, 2020.

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27

Waggoner, Philip D. Unsupervised Machine Learning for Clustering in Political and Social Research. Cambridge University Press, 2020.

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28

Unsupervised Process Monitoring And Fault Diagnosis With Machine Learning Methods. Springer London Ltd, 2013.

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29

Aldrich, Chris, and Lidia Auret. Unsupervised Process Monitoring and Fault Diagnosis with Machine Learning Methods. Springer, 2016.

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30

Vidales, A. Machine Learning with Matlab. Unsupervised Learning: Multidensional Scaling, Dimension Reduction and Cluster Analysis. Independently Published, 2019.

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31

Machine learning Beginners Guide Algorithms: Supervised & Unsupervised learning, Decision Tree & Random Forest Introduction. CreateSpace Independent Publishing Platform, 2017.

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32

Okun, Oleg. Supervised and Unsupervised Ensemble Methods and Their Applications. Springer London, Limited, 2008.

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33

Okun, Oleg. Supervised and Unsupervised Ensemble Methods and their Applications. Springer, 2010.

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34

Applications Of Supervised And Unsupervised Ensemble Methods. Springer, 2009.

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35

Tripathy, B. K., Shrusti Ghela, and Anveshrithaa Sundareswaran. Unsupervised Learning Approaches for Dimensionality Reduction and Data Visualization. Taylor & Francis Group, 2021.

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36

Tripathy, B. K., Shrusti Ghela, and Anveshrithaa Sundareswaran. Unsupervised Learning Approaches for Dimensionality Reduction and Data Visualization. Taylor & Francis Group, 2021.

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37

Tripathy, B. K., Anveshrithaa S, and Shrusti Ghela. Unsupervised Learning Approaches for Dimensionality Reduction and Data Visualization. Taylor & Francis Group, 2021.

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38

Unsupervised Learning Approaches for Dimensionality Reduction and Data Visualization. Taylor & Francis Group, 2021.

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39

Kshatri, 1st Sapna Singh, 2nd Devanand Bhonsle, Roshni Rahangdale Ms 3rd, Tanu Rizvi Ms IV, and V. Ruhi uzma Sheikh. Supervised and Unsupervised Machine Learning Methods and Their Crime Data Applications. INSC International Publisher (IIP), 2022.

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40

Chinnamgari, Sunil Kumar. R Machine Learning Projects: Implement Supervised, Unsupervised, and Reinforcement Learning Techniques Using R 3. 5. Packt Publishing, Limited, 2019.

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41

Pazzani, Michael J., and Douglas H. Jr Fisher. Concept Formation: Knowledge and Experience in Unsupervised Learning (Morgan Kaufmann Series in Machine Learning). Morgan Kaufmann Publishers, 1991.

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42

Bironneau, Michael, and Toby Coleman. Machine Learning with Go Quick Start Guide: Hands-On Techniques for Building Supervised and Unsupervised Machine Learning Workflows. Packt Publishing, Limited, 2019.

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43

Dangeti, Pratap. Statistics for Machine Learning: Techniques for exploring supervised, unsupervised, and reinforcement learning models with Python and R. Packt Publishing, 2017.

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44

Bonaccorso, Giuseppe. Hands-On Unsupervised Learning with Python: Implement Machine Learning and Deep Learning Models Using Scikit-Learn, TensorFlow, and More. Packt Publishing, Limited, 2019.

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45

Okun, Oleg. Applications of Supervised and Unsupervised Ensemble Methods. Springer, 2009.

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46

Okun, Oleg. Applications of Supervised and Unsupervised Ensemble Methods. Springer Berlin / Heidelberg, 2012.

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47

Herreros, Ivan. Learning and control. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780199674923.003.0026.

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This chapter discusses basic concepts from control theory and machine learning to facilitate a formal understanding of animal learning and motor control. It first distinguishes between feedback and feed-forward control strategies, and later introduces the classification of machine learning applications into supervised, unsupervised, and reinforcement learning problems. Next, it links these concepts with their counterparts in the domain of the psychology of animal learning, highlighting the analogies between supervised learning and classical conditioning, reinforcement learning and operant cond
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48

Patel, Ankur A. Hands-On Unsupervised Learning Using Python: How to Build Applied Machine Learning Solutions from Unlabeled Data. O'Reilly Media, 2019.

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49

Signal Processing and Machine Learning for Brain-Machine Interfaces. The Institution of Engineering and Technology, 2018.

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50

Hands-On Unsupervised Learning Using Python: How to Build Applied Machine Learning Solutions from Unlabeled Data. O'Reilly Media, Incorporated, 2019.

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