August 2019
Intermediate to advanced
342 pages
9h 35m
English
As an example of unsupervised learning, we use the GaussianMixture clustering model. Through this type of model, we will try to bring the data back to a collection of Gaussian blobs.
The training data is loaded from a file in .csv format (comma-separated values) and stored in a DataFrame object of the pandas Python library. Once the data is loaded, we proceed to reduce its dimensionality in order to identify a representation that reduces the original dimensions (features) from four to two, trying to maintain the features that are most representative of the samples.
The reduction of dimensionality prevents the disadvantages connected to the phenomenon of the curse of dimensionality, improves the computational ...
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