Chinese Restuarant Process
Bayesian
Unsupervised Learning
In this instance we generate the parameters \[\theta_k\] from \[\mathcal{N}(\mathbf{0},3\mathbf{I})\]. The data is generated from \[\mathcal{N}(\theta_k,0.1\mathbf{I})\]. Where \[k\] is the table. Table allocation is the main part of the CRP which is determined by: \[\begin{align} k=\begin{cases} \text{new table } & \text{with prob = } \frac{\alpha}{\alpha+n-1}\\ \text{table k } & \text{with prob = } \frac{n_k}{\alpha+n-1} \end{cases} \end{align} \] where \[n_k\] is the number of customers at table \[k\].
The associated ipython notebook is located here.