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4. Density estimation
4.1 Classical statistical methods
Recall that density estimation is the very essence of classical statistical analysis: we start with a large number of samples x 1 ,...,x N and investigate which probability distribution these samples correspond to.
Two types of density estimation methods can be distinguished in the low-dimensional field: parametric and non-parametric.
With parametric methods, we think we know in advance the general structure of the density function p θ (x) we're looking for, but this function depends on a certain number of parameters θ, and we try to fix the value of these parameters...
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Density estimation
Generative models
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Software tools
For computations that do not involve deep learning and that deal with data volumes that do not require the use of distributed computing, the two reference software tools are scikit-learn and R
The Spark Mlib library adapts the main machine learning algorithms (excluding deep learning) to a distributed environment, enabling the processing of very large volumes of data.
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