Using Machine Learning to Predict Penguin Species
DOI:
https://doi.org/10.47611/jsrhs.v11i4.3243Keywords:
Computer Science, Machine Learning, Neural Networks, Penguins, Multi ClassificationAbstract
Machine learning is used to make a neural network to predict penguin species from physical attributes. The data set is first prepared, with missing and extraneous data deleted. After this, there remains 333 examples consisting of three different penguin species. These remaining examples are fed into a neural network which proceeds to train on them. The neural network consists of an input and output layer with no hidden layers and uses the softmax activation formula. 25% of the data set is used as a validation set with the remaining 75% used as the training set.
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Müller, A., & Guido, S. (2016). Introduction to Machine Learning with Python: A guide for data scientists. O'Reilly Media
Géron, A. (2019). Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, tools, and techniques to build intelligent systems. O’Reilly Media
Bishop, C. M. (2006). Pattern Recognition and Machine Learning (Information Science and Statistics). Springer Publishing
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Copyright (c) 2022 Alex Hua; Guillermo Goldsztein
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